Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Sun, Feng | Qu, Xiao-bing | Zhu, Ling

Article Type: Research Article

Abstract: Uni-nullnorms generalize both uninorms and nullnorms. In this paper, we investigate the migrativity property for uni-nullnorms. We characterize uni-nullnorms that are α -migrative over a fixed uni-nullnorm, where the 2-neutral elements of uni-nullnorms can be the same or different. Specifically, the (α , V 1 )-migrativity of V when e  = e 1 , a  = a 1 , or e  ≠ e 1 , a  = a 1 or e  = e 1 , a  ≠ a 1 are characterized, where V and V 1 are uni-nullnorms with 2-neutral elements {e , …1}  a and {e 1 , 1}  a 1 , respectively. Show more

Keywords: Uninorms, nullnorms, 2-uninorms, uni-nullnorms, migrativity

DOI: 10.3233/JIFS-190377

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Han, Yefan | Qu, Shaojian | Wu, Zhong | Huang, Ripeng

Article Type: Research Article

Abstract: In the process of group decision making, perturbation of input data always reduces the quality of the optimal solution or even makes it unfeasible. Hence, the value of the optimal solution is often limited. In this paper, a robust optimization method is proposed to overcome the inherent uncertainty of input data in group decision making (such as experts’ unit adjustment cost). Firstly, the minimum cost consensus model based on norm definition is established. Then, four different forms of uncertainty sets are proposed, and the corresponding robust models of four minimum consensus cost models are established. Finally, in order to evaluate …the robustness of the solutions obtained by the robust consensus model, the results with different parameters are compared. The robust consensus model is also compared with the minimum cost consensus model. A numerical example proves that the result of the minimum cost consensus model is too optimistic, and the robust consensus model is more robust. Show more

Keywords: Group decision making, consensus, uncertain set, robust optimization, marketing plan

DOI: 10.3233/JIFS-190863

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Chen, Yubing | Wen, Meilin | Wang, Fei

Article Type: Research Article

Abstract: Data envelopment analysis (DEA) has become an accepted tool for assessing efficiency in a wide range of cases since it was first proposed in 1978. However, traditional DEA models need accurate inputs and outputs, which can’t be obtained or measured in many practical cases. This paper will apply DEA into uncertain environment, and propose a new DEA model with uncertain inputs and outputs based on uncertain theory. Furthermore, the uncertainty theory is utilized to convert the new uncertain DEA model into an equivalent deterministic model for simplification. Finally, this new uncertain DEA model is applied to the evaluation of scientific …research personnel to illustrate the effectiveness. Show more

Keywords: Data envelopment analysis, uncertainty theory, uncertain variable, uncertainty distribution, efficiency

DOI: 10.3233/JIFS-190784

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Wang, Dan | Zhao, Hongwei | Li, Qingliang

Article Type: Research Article

Abstract: This paper designs a brand-new image retrieval method of mammary cancer based on convolution neural network. This method simulates VLAD layer in CNN network structure, designs a trainable universal VLAD layer-NET VLAD layer, reduces dimensions and optimizes VLAD descriptors, applies structure from motion algorithm to automatically label samples, and obtains the minimum loss function value by a new training program of weakly supervised ranking loss. Experiments show that this method has improved retrieval performance compared with similar retrieval methods and non-network structure retrieval methods.

Keywords: Convolutional neural network, VLAD, loss function, medical image retrieval

DOI: 10.3233/JIFS-179386

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Deng, Xilong | Song, Dan | Wei, Li

Article Type: Research Article

Abstract: Befriending with net friends in real life is an important choice for people who live in a fast-paced lifestyle, but results are unsatisfactory and even cause a lot of malignant events. Therefore, this paper simulates the whole process of Internet friend-making through the construction of game model and field experiment, with the aim of showing the behavior logic of people with limited rational when they try to befriend with net friends in real life. This paper aims to give more behavior guidance to related participants. Results from this research show that in the process of making friends on the Internet, …the basis for people befriending with net friends in real life is that they assume that their conditions are equal. But in off-line activities, they cannot improve their effectiveness, which then terminates their communication. Therefore, this paper suggests that Internet social users should distinguish Internet friend-making from traditional friend-making, and do not have too many unrealistic expectations of Internet friend-making. Show more

Keywords: Internet friend-making, actualization, game model, experimental study

DOI: 10.3233/JIFS-179381

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Ma, Xiaohui

Article Type: Research Article

Abstract:  Aggregated search is the task of integrating results from potentially multiple specialized search services, or verticals (images, videos, news, etc.), into the Web search results. Major search engines perform what is known as Aggregated Search. Aggregated search is relatively new and its advantages need to be evaluated. With the increasing size of the data set on the network, different results retrieved from different dimensions are sometimes entirely different for a given search problem. In this paper, a new aggregated search algorithm was proposed. Firstly, the retrieval data in the vertical domain was textualized, and Doc2Vec makes the vector representation of …the data. Then the results are aggregated and output by dimension reduction and density clustering. The experimental results show that the model achieves good accuracy in 20 given queries and significantly improves the aggregated search results. Discussion about the results also allowed us to identify some useful thoughts concerning the evaluation of AS approaches. Show more

Keywords: Aggregated search, dimension reduction, density clustering, information extraction

DOI: 10.3233/JIFS-179380

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Zhao, Dingxuan | Xu, Chunbo | Ni, Tao | Zhang, Hongyan | Qiao, Ruibo

Article Type: Research Article

Abstract: Marine hydraulic manipulator is limited by its size, weight and environment, so traditional hydraulic manipulator cannot be used for marine equipment. In this paper, large displacement pump is replaced by small displacement pump, accumulator is used as absorption pulsation replace by power source, and servo valve is replaced by solenoid valve. In order to improve the dynamic response and control accuracy of the marine hydraulic manipulator. Firstly, the bond graphs model of hydraulic manipulator supplied by oil are established and analyzed. Secondly, the dynamic response characteristics of solenoid valve under different supply voltage are analyzed. Thirdly, the piecewise P optimization …of dynamic response and the fuzzy PI optimization of position control of hydraulic manipulator are carried out. Through piecewise P and fuzzy PI algorithms, not only the dynamic response of the marine manipulator is improved, but also the control accuracy of the marine manipulator is improved. Compared with the traditional hydraulic manipulator, the marine hydraulic manipulator installed volume reduced by 49%, the opening time of solenoid valve is increased by 36%, the response speed is increased by 73%, and the control accuracy is improved by 35%. Show more

Keywords: Piecewise P and fuzzy PI algorithms, accumulator, control accuracy, dynamic response, power bond graph, marine hydraulic manipulator, small pump

DOI: 10.3233/JIFS-179382

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: XinSheng, Zhang | Teng, Gao

Article Type: Research Article

Abstract: Aspect level sentiment classification task require topical polarity classification for different description aspect. There is a polysemy in the same vocabulary, and the emotional polarity is different for different objects. Word embedding can capture semantic information but cannot adapt to the polysemy. Attention mechanism has achieved good performance in the above tasks; however, it is only able to get the degree of association between words and lack able to get details description. In this paper, the ELMOs model is used to adjust the polysemy of the word. The Transformer model is used to extract the features with the highest degree …of relevance to the target object for emotional polarity classification. Our work contribution is to overcome the polysemy interference, and use the attention mechanism to model the network relationship between words, so that the model can extract important classification features according to different target words. Experiments on laptop and restaurant datasets demonstrate that our approach achieves a new state-of-the-art performance on a few benchmarks. Show more

Keywords: Text sentiment classification, fine-grained sentiment analysis, attention mechanism

DOI: 10.3233/JIFS-179383

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Long, Yingwen | Zhu, Yanxiang

Article Type: Research Article

Abstract: The difference of feeder impedance and the nonlinear load may deteriorate reactive power sharing and worsen the power quality, which may cause the breakdown of power supply in islanded microgrids. An enhanced discrete consensus algorithm considering information transmission delay is put forward in order to optimize the convergence dynamic. The proposed algorithm defines the independent iteration number of times variable for every agent, which can be transferred to its adjacent agents together with the communication data to control the times of the iteration calculation. The optimized control strategy is adopted for three-phase distributed generators to balance the reactive power sharing. …Eventually, the simulation results show that the reactive power will be evenly shared among distributed generators in proportion to their rated capacity and the proposed algorithm achieves good dynamic performance during the transition. Show more

Keywords: Reactive power sharing, distributed generator, discrete consensus algorithm, time-delay

DOI: 10.3233/JIFS-179379

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Zang, Jingfeng | Ren, Guibin | An, Yanlin | Piao, Yan

Article Type: Research Article

Abstract: Bad weather has a negative effect on the perceptual quality and degrades the performance of computer vision system. Therefore, a rain removal method based on dual-tree complex wavelet fusion is proposed. The algorithm can be further used for video surveillance system and intelligent transportation and other fields. The method analyzes from the perspective of frequency domain, using the dual-tree complex wavelet decomposition: decomposing images into low frequency sub-images and high frequency sub-images, then developing the different fusion rules. For the low frequency sub-images, fusion rules using the principal component analysis. For the high frequency sub-images, fusion rules using the local …energy matching. In this paper, an image edge enhancement algorithm based on fast guided filter is proposed, a SIFT feature matching method based on maximum likelihood estimation sampling and consistent(MLESAC) algorithm is proposed. Experiments results show that the proposed algorithm can improve the definition of images and restore the details of the target blocked by raindrops. Show more

Keywords: Raindrops removal, dual-tree complex wavelet fusion, PCA, local energy

DOI: 10.3233/JIFS-179385

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Zeng, Jiasheng | Wang, Pei

Article Type: Research Article

Abstract: Rough set theory (for short, RST) are widely applied to artificial intelligence. Fuzzy rough sets (for short, FRSs) are the results of approximation of fuzzy sets on a fuzzy approximation space. In this paper, L -fuzzy is briefly denoted by LF . We study a topological problem of FRSs based on residuated lattices, i.e., suppose that L is a complete residuated lattice, then when may the given LF -topology be consistent with the LF -topology induced by some preorder LF -relation? In order to answer this problem, the notion of LF -approximating spaces is introduced. Moreover, determinant conditions for …LF -topological spaces to be LF -approximating spaces are given. Show more

Keywords: LF-set, LF-topology, LF-approximation space, LF-rough set, LF-approximating space, (C 1) and (C 2) axioms

DOI: 10.3233/IFS-182766

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Zeng, Jun

Article Type: Research Article

Abstract: In order to improve the security of information storage in multi-domain optical network privacy protection, hybrid encoding and encryption of privacy protection information in multi-domain optical network is carried out. A hybrid coding and secure encryption technique based on particle swarm optimization (PSO) for privacy protection information in multi-domain optical network is proposed. The coding mapping equation of privacy protection information security encryption in multi-domain optical network is constructed, and the privacy protection information of multi-domain fiber network is loaded into the coding mapping equation of security encryption of privacy protection information in multi-domain fiber network. A set of characteristic …solutions describing the entropy function of the characteristic distribution of random encryption keys are obtained, and the elliptic mapping random linear combination coding and chaotic encryption key allocation are carried out. The privacy protection method of multi-domain optical fiber network is used to encrypt and decode information with mixed coding and steganography. Under the bilinear mapping coding system, the privacy-protected information in multi-domain optical network is encrypted and encrypted, stored and transmitted confidently. The simulation results show that this encryption technique has better steganography performance and better secure transmission and storage performance for the privacy protection information mixed encoding encryption in multi-domain optical network. Show more

Keywords: Particle swarm optimization algorithm, multi-domain fiber optic network, secure encryption

DOI: 10.3233/JIFS-179388

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Wang, Zhongru | Ruan, Qiang

Article Type: Research Article

Abstract: Communication network security is an important part of the digital signal processor. In particular, the process bus replaces the traditional hard wiring, which makes the network system extend from the second to the first time, greatly increasing the network scale and network traffic; the information transmitted on the process bus is absolutely large. Most requirements require strict real-time and high reliability. Therefore, information security is a major problem that threatens the security, stability, economy, and quality operation of network systems, and needs to be paid enough attention. This paper introduces the methods of information classification and information merging to improve …the real-time information. It proposes to apply network security technologies such as information encryption technology, firewall technology, mobile agent, security management technology and virtual private network (VPN) technology to office network of the electric-power industry and analysed the specific application scenarios and effects. Show more

Keywords: Network video surveillance, embedded system, digital signal processor, network security subsystem

DOI: 10.3233/JIFS-179384

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Kemal Ozdemir, M. | Esi, Ayhan | Subramanian, Nagarajan

Article Type: Research Article

Abstract: There are several notions of convergence of fuzzy number sequences in the literature. The aim of this paper is to introduce and study a new concept of the rough fuzzy ideal convergent triple sequences defined by Orlicz function. Also, some topological properties of the resulting sequence spaces of rough fuzzy numbers were examined.

Keywords: Triple sequences, rough convergence, fuzzy numbers, Orlicz function, difference sequence, duals, integral sequence, 40F05, 40J05, 40G05

DOI: 10.3233/JIFS-182832

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Wang, Dan | Zhao, Hongwei | Li, Qingliang

Article Type: Research Article

Abstract: This paper presents a medical brain image algorithm based on multi-feature fusion. Feature extraction based on convolutional neural network was used as texture information, feature extraction based on voxel information was used as morphological feature, and then the two types of features were combined in series. Feature extraction based on convolutional neural network was used as texture information, feature extraction based on voxel information was used as morphological feature, and then the two types of features were combined in series. Then the heuristic search algorithm is used to optimize the feature selection stage. Based on the feature score table extracted …by the recursive feature elimination method of support vector machine, the correlation between features is added. Moreover, through experimental analysis, the optimal value of the parameter K was selected according to the heuristic search, and the optimal feature subset was extracted after determining the value of the parameter K. Experiments show that compared with similar algorithms, this algorithm improves the accuracy and efficiency of the classification of brain images. Show more

Keywords: Convolutional neural network, multi-feature fusion, heuristic search, medical image classification

DOI: 10.3233/IFS-179387

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Aaly Kologani, M. | Jun, Y.B. | Xin, X.L. | Roh, E.H. | Borzooei, R.A.

Article Type: Research Article

Abstract: In this paper, we introduce the notion of co-annihilator in hoops and investigate some related properties of them. Then we prove that the set of filters F ( A ) form two pseudo-complemented lattices (with ∗ and ⊤) that if A has (DNP), then the two pseudo-complemented lattices are the same. Moreover, by defining the operation → on the lattice F ( A ) , we prove that F ( A ) is a Heyting algebra and by defining of the product operation, we show …that F ( A ) is a bounded hoop. Finally, we define the C  - Ann  (A ) to be the set of all co-annihilators of A , then we have that it had made a Boolean algebra. Also, we give an extension of a filter, which leads to a useful characterization of α -filters on hoops. For instance, we obtain a series of characterizations of α -filters. In addition, we show that there are no non-trivial α -filters on hoop-chains. That implies the structure of all α -filters contains only trivial α -filters on hoops. On hoops, we prove that the set of all α -filters is a pseudo-complemented lattice. Moreover, the structure of all α -filters can form a Boolean algebra under certain conditions. Show more

Keywords: Hoop, Boolean algebra, Heyting algebra, filter, co-annihilator, pseudo-complement

DOI: 10.3233/IFS-190565

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Dong, Shi | Jain, Raj

Article Type: Research Article

Abstract: Community detection is of great importance to understand the structures and functions of networks. Overlap is a significant feature of networks and overlapping community detection has attracted an increasing attention. Although many algorithms have been presented to detect overlapping communities, detection of overlapping community is still a challenging task. It can not efficiently obtain the latest community structure that the traditional static method partition the network structure. Therefore, this paper presents a new overlapping community detection algorithm based on improved KNN, the algorithm can timely adjust community structure based on different networks change, and ultimately obtains the results of the …community partition with high degree of Q module. Show more

Keywords: Social networks, overlapping community, community detection, Q module

DOI: 10.3233/JIFS-190724

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Li, Yonghong | Li, Jiang | Duan, Huiming | Qiu, Dong

Article Type: Research Article

Abstract: The purpose of this paper is to study matroids on intuitionistic fuzzy sets, so as to generalize G  - V fuzzy matroids.The ranking, union and intersection between two intuitionistic fuzzy sets are firstly defined by using the similarity function h and the accuracy function H of the intuitionistic fuzzy value. Then a G  - V intuitionistic fuzzy matroid which can be regarded as an extension of G  - V fuzzy matroids is proposed. Particularly, the induced matroid sequence and the rank function of a G  - V intuitionistic fuzzy matroid and their properties are studied.

Keywords: Fuzzy set, intuitionistic fuzzy set, matroid, fuzzy matroid, G - V intuitionistic fuzzy matroid, rank function

DOI: 10.3233/JIFS-182798

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Sakr, Nehal A. | Abu-Elkheir, Mervat | Atwan, A. | Soliman, H. H.

Article Type: Research Article

Abstract: Sensor-based human activity recognition gained a lot of research interest within the field of pervasive computing due to its wide range of application domains. Recognition of complex human activities is a challenging task due to the tendency of humans to perform activities in an interleaved and concurrent scenario. In this paper, we address the problem of complex activities recognition using a combination of the discriminative features called Strong Jumping Emerging Patterns (SJEPs) and the fuzzy sets theory. The proposed approach is designed to fit the challenges of multi-label classification, nonlinear separation, and recognition of multiple overlaps of interleaved and concurrent …activities. Besides the need for a training dataset of complex activities that is difficult to obtain. The proposed approach uses a training dataset of simple activities to extract two sets of SJEPs for linear and nonlinear activities. Then, a novel SJEP-based recognition approach is presented to recognize simple and complex activities. We evaluate our approach using two datasets collected from two different labs. Experimental results show the efficiency of our approach in recognizing simple and complex human activities, besides the superiority of our approach against other competing approaches with regard to recognition accuracy. Show more

Keywords: Complex activities recognition, emerging pattern, multi-label classification, nonlinear separation, fuzzy sets

DOI: 10.3233/JIFS-190706

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Darestani, Soroush Avakh | Mousazadeh, Saeed

Article Type: Research Article

Abstract: Blood and blood products are vital resources for the surgery and the treatment of certain diseases. As a scarce and perishable resource, they require sophisticated management to minimize waste in order to address this challenge, the present study revolves around the idea of the management of the production, supply and distribution of blood products. In this research, two questions of robust and flexible have been investigated for the production, inventory and routing blood products. The flexibility is incorporated into the problem through introducing the possibility of sharing inventory among network entities by transferring blood products between hospitals and also the …possibility of meeting a blood group’s need with another compatible blood type or replacement. The problem is then solved by heuristic (local search) and meta-heuristic (Adaptive Large Neighborhood Search (ALNS)) algorithms, which are the methods of choice in particular for NP-hard problems. Finally, the results obtained from the two algorithms are compared it is shown that the heuristic algorithm outperforms the Adaptive Large Neighborhood Search (ALNS) in both models, that can lead to reduction is cost and required transitions. Show more

Keywords: Inventory, routing, integrated production, routing, robust optimization, health care optimization, flexibility, uncertainty

DOI: 10.3233/JIFS-190723

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-21, 2019

Authors: López-Medina, M.A. | Espinilla, M. | Cleland, I. | Nugent, C. | Medina, J.

Article Type: Research Article

Abstract: Fog Computing is an approach involving smart devices. These devices carry out data processing to provide collaborative services to reach a common goal, usually, in the cloud. In the fog computing paradigm, uncertainty and vagueness are inherent to the data processing due to the limitations of computational and communication capabilities of the smart devices. Fuzzy logic and protoforms represent a powerful tool to model and compute imprecise data presented within the fog-computing paradigm. In this paper, we present a fuzzy cloud-fog approach based on fuzzy temporal windows and fuzzy aggregation. The innovations of this paper are: i) to model the …uncertainty involved in fog nodes linguistically, ii) to compute and distribute relevant linguistic information (protoforms), and iii) to publish the computed protoforms in the cloud to generate complex protoforms, which reach the common goal. This new fuzzy cloud-fog approach is applied to the problem of activity recognition in smart homes. In this context, the smart devices in a smart home are represented by fog nodes, which cooperate for activity recognition using a fuzzy cloud-fog computing approach to provide solutions in ambient-assisted living. Finally, to demonstrate the effectiveness of the proposal in handling situations/environments where multiple and heterogeneous devices are involved (such as UWB beacons, smart objects and smart wearable devices), a case study of the proposed fuzzy cloud-fog approach is implemented in the smart lab of the University of Jaén. So, the results obtained with the proposed approach in the case study are compared to the results obtained with a non-fuzzy approach with the aim of showing the advantages of the fuzzy methodology. Show more

Keywords: Fuzzy fog computing, fuzzy cloud computing, smart devices, UWB technology, activity recognition, protoforms, fuzzy temporal windows, fuzzy aggregation

DOI: 10.3233/JIFS-179443

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Hu, Bo | Bi, Lvqing | Dai, Songsong

Article Type: Research Article

Abstract: This paper presents the notion of approximate orthogonality of complex fuzzy sets, which is a generalization of the existing concept. Based on the new concept, we present some basic properties of the approximate orthogonality of complex fuzzy sets. Furthermore, we discuss approximately orthogonality preserving with respect to complement, union and intersection operations of complex fuzzy sets.

Keywords: Complex fuzzy sets, operators, approximate orthogonality, approximately orthogonality preserving

DOI: 10.3233/JIFS-182643

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Riaz, Muhammad | Raza Hashmi, Masooma

Article Type: Research Article

Abstract:  The prevailing concepts of intuitionistic fuzzy sets (IFSs), Pythagorean fuzzy sets (PFSs) and q-rung orthopair fuzzy sets (q-ROFSs) have numerous applications in various fields from real life. Unfortunately, these theories have their own limitations related to the membership and non-membership grades. To eradicate these restrictions, we introduce the novel concept of linear Diophantine fuzzy set (LDFS) with the addition of reference parameters. This idea removes the restrictions of existing methodologies and the decision maker (DM) can freely choose the grades without any limitations. This structure also categorizes the problem by changing the physical sense of reference parameters. We present some …fundamental operations on linear Diophantine fuzzy sets (LDFSs). We present geometrical interpretation for different operations of LDFSs. We also introduce the novel concepts of linear Diophantine fuzzy topological space (LDFTS) and linear Diophantine fuzzy weighted geometric aggregation (LDFWGA) operator. We discuss several properties of LDFTS with the help of examples. We introduce score functions and accuracy functions with different orders for the comparison of linear Diophantine fuzzy numbers (LDFNs). We propose two algorithms for solving multi-attribute decision-making (MADM) problem accompanied by an interesting application employing LDFTSs and LDFWGA operator. Show more

Keywords: Linear Diophantine fuzzy set (LDFS), geometrical interpretation of LDFS, linear Diophantine fuzzy topological space (LDFTS), linear Diophantine fuzzy weighted geometric aggregation (LDFWGA) operator, MADM

DOI: 10.3233/JIFS-190550

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-23, 2019

Authors: Zhong, Yanru | Guo, Xiuyan | Gao, Hong | Qin, Yuchu | Huang, Meifa | Luo, Xiaonan

Article Type: Research Article

Abstract: To describe the values of criteria and to generate a sort of alternatives are two important issues in multi-criteria decision-making (MCDM). A superior tool for the former issue is Pythagorean hesitant fuzzy number (PHFN) and an effective tool for the latter issue is aggregation operator. So far, a number of aggregation operators of PHFNs have been presented within the academia. Each aggregation operator has its own characteristics and can work well for its specific purpose. But there is not yet an aggregation operator of PHFNs that can provide satisfying generality and flexibility in aggregating the values of criteria and capturing …the interactions of criteria. The Archimedean t-conorm and t-norm (ATT) are well-known for having the capability to generate versatile and flexible operational rules for fuzzy numbers, while the Muirhead mean (MM) operator is an all-in-one aggregation operator for capturing the interrelationships of the aggregated arguments. To this end, the MM operator and the ATT for PHFNs are combined to present a Pythagorean hesitant fuzzy Archimedean MM (PHFAMM) operator and a weighted PHFAMM operator and a new MCDM method based on the presented operators is proposed in this paper. Firstly, the generalised expressions of the presented operators are provided. The properties of the operators are explored and proved and their specific expressions based on Algebraic, Einstein, Hamacher, and Frank ATTs are then constructed. Based on these specific expressions, a new method for solving the MCDM problems based on PHFNs is developed. Finally, the developed MCDM method is demonstrated via an example, a set of experiments and qualitative and quantitative comparisons. Show more

Keywords: Pythagorean hesitant fuzzy set, muirhead mean operator, Archimedean t-conorm and t-norm, aggregation operator, multi-criteria decision-making

DOI: 10.3233/JIFS-190704

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-21, 2019

Authors: Ðurić, Goran | Mitrović, Časlav | Komatina, Nikola | Tadić, Danijela | Vorotović, Goran

Article Type: Research Article

Abstract: Evaluation and analysis of failures which occur in the products or services in different economic areas are an important task of operational management. Solution of this problem leads to the increase of product’s/service’s quality, but in the same time it also increases business processes effectiveness and business goal’s realization. The treated problem is especially important in the information technologies domain. In this paper, the risk factors that may cause failures of the software are defined in compliance with the Failure Mode and Effect Analysis (FMEA) framework and they are assessed during the development and the maintenance phase. The relative importance …of these risk factors and their values at the level of each identified failure are described by pre-defined linguistic terms which are modelled by the interval type-2 trapezoidal fuzzy numbers (IT2TrFNs). The weights vector is calculated by using the Fuzzy Analytic Hierarchy Process (FAHP) with interval type-2 fuzzy sets. The rank of failures is obtained by using the complex proportional assessment (COPRAS) method. The example with real life data is illustrated to demonstrate the potential and applicability of the adopted methods. Show more

Keywords: MCDM, failures, software, FMEA, type-2 trapezoidal fuzzy numbers

DOI: 10.3233/JIFS-182541

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Wang, Bing | Li, Qing-Hua

Article Type: Research Article

Abstract: The aim of this paper is to study the relations among soft topological spaces, soft L -topological spaces and stratified soft L -topological spaces. Firstly, we construct a Galois correspondence between the category SoTop of soft topological spaces and the category So L -Top of soft L -topological spaces, and obtain that SoTop is a coreflective subcategory of So L -Top . Secondly, we show that there is a Galois correspondence between the category SSo L -Top of stratified soft L -topological spaces and SoTop and obtain that SoTop is a …reflective subcategory of SSo L -Top . Finally, we study the stratification of soft L -topological spaces. We also construct a Galois correspondence between SSo L -Top and So L -Top , and obtain that SSo L -Top is a coreflective subcategory of So L -Top . Show more

Keywords: Soft topology, (Stratified) Soft L-topology, Galois correspondence, Reflective, Coreflective

DOI: 10.3233/JIFS-182887

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Xiaobing, Yu | Xianrui, Yu | Hong, Chen

Article Type: Research Article

Abstract: Gravitational search algorithm (GSA) is inspired by swarm behaviors in nature and physical law based on Newtonian gravity and the laws of motion. There are two key parameters including the number of applied agents (Kbest ) and gravitational coefficient (G ) to control the search progress in the algorithm. In the conventional GSA, the acceleration of the agents is mainly determined by Kbest and G. Kbest and G are calculated by a monotonically decreasing function, which is not a good schedule for solving complex problems. In order to solve the problem and accelerate the convergence of …algorithm, an adaptive GSA is proposed, in which Kbest and G calculation method for strengthening exploitation capability are implemented to achieve better optimization results. Extensive experimental results based on benchmark functions are provided to show the effectiveness of the proposed method. The obtained results have been compared with the results of the original GSA, CGSA, and CLPSO. The comparison results have revealed that the proposed method has good performances. Show more

Keywords: Heuristic optimization algorithm, gravitational search algorithm, gravitational coefficient, global optimization

DOI: 10.3233/JIFS-182779

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Jiang, Chunmao | Duan, Ying | Yao, Jun

Article Type: Research Article

Abstract: Task clustering is an effective approach of improving cloud computing resource utilization, which include other benefits such as better QoS, load balance and low energy consumption. Different existing clustering methods have sharp boundaries, three-way clustering as an application of three-way decision, uses core region and fringe region to represent a cluster. In this paper, we propose a novel idea of clustering weight algorithm called TWCW algorithm(Three-way clustering weight) based on three-way decision to overcome the low utilization aiming at improving energy-efficient. The algorithm encompass two steps, the identified tasks are assigned into the core region and the uncertain tasks are …assigned into the fringe region based on diversity of cloud tasks and the dynamic nature of resources using the three-way K-means clustering firstly. The cluster center of CS i , centroid i  = {mips , ram , bw } is obtained from the result of three-way clustering. In the second step is to score clusters and schedule tasks. We define a scoring matrix to record scores of the weight between clusters and the preference of attributes within clusters according to the cluster center, and then schedule tasks based on scoring matrix. We validate the high utilization of resoures of the proposed algorithm by using simulation of CloudSim. The experiment shows the proposed algorithms significantly reduce energy consumption while significant improving response time of tasks comparing with K-means algorithm and FCM algorithm. Show more

Keywords: Cloud computing, three-way clustering, three-way decisions, task schedule, average response time, task sets

DOI: 10.3233/JIFS-190459

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Abdi, M. | Allahviranloo, T.

Article Type: Research Article

Abstract: In this paper, first, the fuzzy Poisson’s equation and the fuzzy finite difference method are introduced. Then, the fuzzy Poisson’s equation is discretized by fuzzy finite difference method and it is solved as a linear system of equations. In addition, we discuss fuzzy Laplace equation as a special case of fuzzy Poisson’s equation. Finally, the convergence of method is taken into account and for more illustration a numerrical example is solved.

Keywords: Fuzzy number, fuzzy poisson’s equation, fuzzy finite difference method, convergence, fuzzy divergence theorem

DOI: 10.3233/JIFS-190408

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Lin, Yidong | Li, Jinjin

Article Type: Research Article

Abstract: Granular reduction is an important issue for knowledge representation and data analysis in formal concept analysis. Granular structure of crisp-fuzzy concepts with application in granular reduction in formal fuzzy contexts is examined in this paper. However, computing a minimal granular reduct of a formal fuzzy context by Boolean reasoning is an NP-hard problem. Therefore, it is natural to investigate a heuristic approach to deal with this problem. A new method based on Boolean matrix is proposed to search the granular reduction. Granular matrix representations for extensions and intensions are firstly proposed. Then, we develop a similar degree between attribute subsets …to measure attribute significance. Subsequently, two heuristic algorithms for granular reduction in formal fuzzy contexts and formal fuzzy decision contexts are presented, respectively. We prove that the time complexities of the algorithms are polynomial. Finally, numerical experiments demonstrate the proposed algorithms are much more feasible and efficient. Our methods present a new framework for granular reduction in formal fuzzy contexts. Show more

Keywords: Boolean matrix, crisp-fuzzy concept, formal fuzzy context, granular reduction, Heuristic algorithm

DOI: 10.3233/JIFS-190161

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Zheng, Qinghe | Tian, Xinyu | Jiang, Nan | Yang, Mingqiang

Article Type: Research Article

Abstract: Nowadays, despite the popularity of deep convolutional neural networks (CNNs), the efficient training of network models remains challenging due to several problems. In this paper, we present a layer-wise learning based stochastic gradient descent method (LLb-SGD) for gradient-based optimization of objective functions in deep learning, which is simple and computationally efficient. By simulating the cross-media propagation mechanism of light in the natural environment, we set an adaptive learning rate for each layer of neural networks. In order to find the proper local optimum quickly, the dynamic learning sequence spanning different layers adaptively adjust the descending speed of objective function in …multi-scale and multi-dimensional environment. To the best of our knowledge, this is the first attempt to introduce an adaptive layer-wise learning schedule with a certain degree of convergence guarantee. Due to its generality and robustness, the method is insensitive to hyper-parameters and therefore can be applied to various network architectures and datasets. Finally, we show promising results compared to other optimization methods on two image classification benchmarks using five standard networks. Show more

Keywords: Deep learning, deep CNNs, non-convex optimization, SGD, layer-wise learning

DOI: 10.3233/JIFS-190861

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Saleem, Nasir | Irfan Khattak, Muhammad | Qazi, Abdul Baser

Article Type: Research Article

Abstract: In real-world situation, speech signals reaching our ears are usually degraded by the background noise. These distortions are detrimental to the speech quality and intelligibility and also cause a serious problem to many speech-related applications, such as automatic speech recognition and speaker identification. In order to deal with the background noise distortions, we propose a strategy to enhance the degraded speech in this paper, where speech enhancement is conducted using supervised deep neural network models. The models are trained to learn a mapping from the features of noisy speech to estimate the ideal-ratio mask (IRM). The estimated IRM is then …applied to the noisy speech in order to obtain an enhanced version of the degraded speech. The mean square error (MSE) is used as an objective cost function. Additionally, Global Variance Equalization is performed as a post-processing step to equalize variances of the features. Systematic evaluations and comparisons show that the proposed supervised method improves objective metrics of speech quality and intelligibility substantially and significantly outperforms the competing and baseline speech enhancement methods. Finally, the proposed method is examined in speaker identification task in noisy situations. The proposed method leads to the highest speaker identification rates when compare to the competing and baseline speech enhancement methods. Show more

Keywords: Speech enhancement, deep neural networks, supervised learning, global variance, quality, intelligibility

DOI: 10.3233/JIFS-190047

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Gałka, Jakub | Jaciów, Paweł

Article Type: Research Article

Abstract: In this paper, we propose a new method for concurrent accuracy and computational efficiency optimization using a fuzzy clusters tree for i-vector speaker identification. The design assumptions and an algorithm for a new type of fuzzy i-vector tree construction were introduced. The obtained solution was evaluated using the NIST 2014 i-Vector Speaker Recognition Machine Learning Challenge dataset. A 15% relative equal error rate reduction for a 74% reduction in computation time was achieved when compared to the baseline with only a 5.5% relative identification rate loss for discussed tree configurations.

Keywords: speaker recognition, fast identification, i-vector, fuzzy clustering, decision trees

DOI: 10.3233/JIFS-181359

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Riaz, Muhammad | Hashmi, Masooma Raza

Article Type: Research Article

Abstract: In multi-attribute group decision-making (MAGDM) problems, there exist some multi-polarity for the attributes and criteria. Sometimes in real life situations, we deal with the both membership and non-membership grades for the attributes in the presence of multi-polarity. For this purpose, we change verbally stated information into mathematical language with the help of uncertain linguistic variables to deal with the ambiguities and uncertainties. In that case, we construct some extensions from the existing hybrid structures of fuzzy set to handle these types of problems. That’s why from the prevailing concepts of cubic set and m-polar fuzzy set, we innovate the concept …of cubic m-polar fuzzy set (CMPFS). We investigate its numerous operations with the help of examples. With the enthusiasm of CMPFS, we establish certain aggregation operators based on cubic m-polar fuzzy numbers (CMPFNs) namely Cubic m-polar fuzzy weighted averaging (CMPFWA), Cubic m-polar fuzzy ordered weighted averaging (CMPFOWA) and Cubic m-polar fuzzy hybrid averaging (CMPFHA) operators corresponding to R -order and P -order, simultaneously. Using the score function and accuracy function a relation is proposed, through which we can compare the CMPFNs. This manuscript presents a novel approach for treating ambiguities based on the application of land selection using linguistic variables in CMPF decision theory. An algorithm based on MAGDM is intended for a given agricultural project, which will produce results according to the proposed operators one by one. Furthermore, a comparative analysis is listed to demonstrate the difference, advantages, validity, simplicity, flexibility and superiority to the proposed operators. Show more

Keywords: Cubic m-polar fuzzy set (CMPFS), membership degrees, Cubic m-polar fuzzy weighted averaging (CMPFWA) operator, Cubic m-polar fuzzy ordered weighted averaging (CMPFOWA) operator and Cubic m-polar fuzzy hybrid averaging (CMPFHA) operator, MAGDM for agricultural purpose

DOI: 10.3233/JIFS-182809

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-21, 2019

Authors: Nair, Shyni P | Mary Linda, M.

Article Type: Research Article

Abstract: This paper proposes a hybrid strategy based maximum power point tracking (MPPT) control algorithm technique to extricate maximum power from the high infiltrating hybrid renewable energy system. The proposed hybrid strategy is the mix of Modified Dragonfly Algorithm (MDA) and Recurrent Neural Network (RNN) named as MDA-RNN. In the proposed MDA learning based RNN approach, the learning process of the RNN is upgraded by the MDA optimization process dependent on the minimum error objective function. Here, the proposed procedure precisely tracks the duty cycles of the hybrid renewable energy system utilizing Enhanced High Boost (EHB) DC-DC converter to extricate the …maximum power output from the sources. To achieve this MPPT procedure, the proposed technique requires the hybrid renewable energy system power flow parameters varieties like voltage and current at each time interim. This control system additionally consolidates a Particle Swarm Optimization (PSO) and levy flight approaches to deal with minimizing the losses in the generator and subsequently to improve the productivity of the wind and PV system. At long last, the execution of the proposed MPPT control of wind and PV power generation plans is executed in MATLAB/Simulink working stage and the execution is surveyed with the current systems. Show more

Keywords: Hybrid renewable energy system, maximum power point tracking, modified dragonfly algorithm, recurrent neural network, Enhanced High Boost (EHB) DC-DC converter

DOI: 10.3233/JIFS-190591

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2019

Authors: Vu, Ho | Hoa, Ngo Van | An, Truong Vinh

Article Type: Research Article

Abstract: The results of this paper is motivated from some recent papers treating the problem of the existence and stability of a solution for Volterra integro-differential equations in fuzzy setting with fractional order derivative (FFVIDEs). By constructing successive approximation method in the space of fuzzy functions, we establish the Ulam-Hyers stability and Ulam-Hyers-Rassias stability for the given problems with two concepts of fuzzy-type fractional derivative.

Keywords: Ulam-hyers stability, ulam-hyers-rassias stability, fuzzy fractional integro-differential equations

DOI: 10.3233/JIFS-190952

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2019

Authors: Nadeem, Farrukh

Article Type: Research Article

Abstract: Today’s large scale distributed platforms comprise thousands of resources from production, educational, and ad hoc environments including Clouds, Grids, P2P, etc. However, finding suitable resources from such a large pool to store large amounts of data and run multi-resource, long-running data processing applications (usually with few or no fault tolerance capabilities) is restricted by the dynamic availability of distributed resources. In addition to resource failures, the resources may be unavailable due to their owners’ policies for sharing their resources as well as the nature of domain they belong to (e.g. P2P systems, non-dedicated desktop Grids etc.). As a result, the …availability-aware selection of distributed resources has become a challenging problem for data management, resource provisioning and job scheduling services. To this end, we present a novel resource availability characterization and prediction method for dynamic heterogeneous distributed environments. We identified 14 availability attributes that can be effectively used to model resource availability in dynamic distributed environments. Three data mining methods (particularly the neural network) are proposed to model and predict resource availability in terms of our identified availability attributes. The availability of a resource is predicted for an instant of time as well as for a time duration. Our experiments for 28 different resources in Austrian Grid show that the predictions through the proposed approach are 18% and 31% (on average) more accurate than those by so far the best method (Naive Bayes’ Classifier) for instant and duration availability, respectively. Show more

Keywords: Distributed systems, dynamic resource availability, resource availability characterization, resource availability predictions

DOI: 10.3233/JIFS-190749

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Too, Edna C. | Yujian, Li | Kwao, Pius | Njuki, Sam | Mosomi, Mugendi E. | Kibet, Julius

Article Type: Research Article

Abstract:  Deep learning is a field of Artificial Intelligence that has recently drawn a lot of attention with the desire to build up a quick, automatic and accurate system for image identification and classification. Deep learning serves as a fundamental part of modern computer vision solutions. However, as the architectures become deep and powerful new challenges in the process of training emerge. This includes the computational cost associated with training deep and large networks. In this work, the focus is on pruning and evaluation of state-of-the-art deep convolutional neural network for image-based plant disease and plants species classification. Pruning filters allow …the reduction of parameters by removing unimportant filters and its feature maps. In this paper, the performance of pruned networks is evaluated across three datasets. It is observed that pruned DenseNet with Self-Normalization Neural Network (SNN) approach learns 2x faster compared to the initial DenseNet architecture. Additionally, pruning filters allow the reduction of the number of parameters and FLOPs by approximately 14% and 25% respectively. The aim is to create a fast and efficient model for the purpose of identification of plant diseases. Fast methods are desired for early identifications of diseases before damages occur. The proposed method achieves a satisfactory accuracy performance on PlantVillage, LeafSnap and Swedish-leaf dataset using held-out dataset. Our best pruned model gives an accuracy of 99.24%, 86.64%, and 97.5% on PlantVillage, LeafSnap, and Swedish-leaf datasets respectively. Show more

Keywords: Deep learning, convolutional neural network, pruning, image-based disease classification

DOI: 10.3233/JIFS-190184

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2019

Authors: Kim, Young Ho

Article Type: Editorial

Abstract: This special issue of the Journal of Intelligent & Fuzzy Systems contains selected articles of fuzzy logic for analysis of clinical diagnosis and decision-making in health care.

DOI: 10.3233/JIFS-179374

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-2, 2019

Authors: Tao, Hong-Yu | Zhao, Mei-Ling | Ye, Jun

Article Type: Research Article

Abstract: A neutrosophic cubic set (NCS) can depict single-valued and interval neutrosophic information simultaneously in real life. Then, the NCS concept cannot describe neutrosophic cubic information regarding the assessment problems of two-dimensional universal sets (TDUSs), while a Q-neutrosophic set (Q-NS) can depict neutrosophic information in TDUSs but not describe neutrosophic cubic information in TDUSs. Motivated by the Q-NS and NCS concepts, we need to extend the Q-NS concept to Q-NCS for indicating neutrosophic cubic information in TDUSs. Therefore, this study first proposes a Q-NCS concept, which indicates its truth, falsity, and indeterminacy values independently in TDUSs, and then the basic operations …of Q-neutrosophic cubic elements (Q-NCEs) and some weighted aggregation operators of Q-NCEs, such as a Q-NCE weighted arithmetic averaging (Q-NCEWAA) operator and a Q-NCE weighted geometric averaging (Q-NCEWGA) operator. Next, Q-neutrosophic cubic multi-attribute decision-making (MADM) methods regarding the proposed Q-NCEWAA and Q-NCEWGA operators are proposed under TDUSs and Q-NCS setting. Eventually, an illustrative example shows the applicability of the proposed MADM methods in TDUSs and Q-NCS setting. Show more

Keywords: Q-neutrosophic cubic set, two-dimensional universal sets, Q-neutrosophic cubic element weighted geometric averaging (Q-NCEWAA) operator, Q-neutrosophic cubic element weighted geometric averaging (Q-NCEWGA) operator, decision making

DOI: 10.3233/JIFS-190116

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Sun, Yixiang | Geng, Nana | Gong, Shuli | Yang, Yinbao

Article Type: Research Article

Abstract: At present, airlines cannot meet the requirements of increasing air cargo volume and cargo service quality by simply improving air transportation capacity. On the basis of increasing the construction of aviation logistics distribution centers, airlines also need to optimize the distribution route. By analyzing and comparing the application of genetic algorithm in the problem of distribution path optimization, this paper proposes a new adaptive genetic algorithm with adaptive mutation to improve the search ability in the local range, which has faster convergence speed than the general genetic algorithm. And solve the logistics node location model. The result proves that the …algorithm is faster and more accurate, and can solve the transportation path problem in distribution. Show more

Keywords: Improved genetic algorithm, distribution center, path optimization, aviation logistics

DOI: 10.3233/JIFS-179377

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Zhao, Lei

Article Type: Research Article

Abstract:  The article combines mathematical models to describe the multi-customer air cargo routing problem. Aiming at the coding problems in standard genetic algorithms and the large number of non-feasible solutions after crossover and mutation, this paper proposes a new feasible method–two-generation competition and steady-state genetic operator design. Finally, the model solving method and steps based on improved genetic algorithm are given. The example calculation shows that the method can provide scientific and effective support for the decision of the route selection problem in the air cargo system.

Keywords: Improved genetic algorithm, multi-user transportation, air cargo, route optimization

DOI: 10.3233/JIFS-179378

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Zhang, Nian | Yuan, Yin | Fu, Deqiang | Wei, Guiwu

Article Type: Research Article

Abstract: Dual hesitant fuzzy linguistic set consists of linguistic terms, membership hesitancy degrees and non-membership hesitancy degrees, which is widely applied to describe the quantitative and qualitative information in the decision-making problem. In this article, some new power aggregation operators of dual hesitant fuzzy linguistic set on the Archimedean t-conorms and t-norms functions are introduced. Then, the properties of those new operators are studied and the relationships between novel operators and existing ones are discussed. Furthermore, an approach to resolve group decision making problem is described. Finally, an example is used to illustrate the developed approach.

Keywords: Dual hesitant fuzzy linguistic set, power-geometric operator, Archimedean t-conorm and t-norm, group decision making

DOI: 10.3233/JIFS-190098

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2019

Authors: Yang, Yingfa

Article Type: Research Article

Abstract: The facial information of a person has constant invariance, and at the same time, it is an ideal basis for identifying identity information through differences between different individuals. The use of face recognition in third-party payment platforms will greatly improve the efficiency and security of payment. Based on this, the paper studies and designs the third-party payment system for face recognition in the context of Internet artificial intelligence to improve the convenience and security of face payment.

Keywords: Internet, artificial intelligence, face payment, face recognition, third party payment system

DOI: 10.3233/JIFS-179376

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Wu, Qidi | Li, Yibing | Lin, Yun

Article Type: Research Article

Abstract: Medical image restoration is a fundamental issue in the area of medical signal processing, which aims recove high quality medical image from its degradation observation. Recently, the methods with nonlocal self-similarity prior have led to a great improvement on many medical image restoration tasks. Nevertheless, the nonlocal technique is generally embedded with only one kind of constraint, such as sparsity or low-rank in the conventional model, which limits their abilities and show good performance on certain prior. To address this problem, in this paper, we present a novel medical image restoration method with multiple nonlocal-based prior regularizations. The surfacelet transformation …is introduced to construct a cubic sparsity constraint to a group of nonlocal similar patches. Likewise, due to the self-similarity existed in the medical image, two extra kinds of nonlocal-based priors, nonlocal total variation and nonlocal weighted low-rank, are also exploited to constrain the local smoothness and nonlocal relationship jointly. In this way, each of the designed priors can well recover a group of patches with similar structure. And then, the designed priors are combined into a unified proposed optimization framework, which will obtain the advantages from all of them simultaneously. Finally, to solve the objective function in the proposed framework, we develop an iterative numerical scenario based on alternating direction multipliers method. The extensive experiments on test medical images demonstrate that our proposed model outperforms the comparison methods on both of visual quality and objective evaluation results. Show more

Keywords: Medical image restoration, nonlocal prior, low-rank, sparsity, surfacelet transformation

DOI: 10.3233/JIFS-179375

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Asif, Muhammad | Shah, Tariq

Article Type: Research Article

Abstract: Accelerated adventures in computer Science and technology has made digital technology, a need of the day. Academicians, researchers, and technologists are anxious to share their secret data through the communication channel along with its security. The security of data, transmission rate, and error correction capability are the fundamental questions against the data transmission through any algebraic code dependent communication channel. Though, data security is always questioned due to the synchronized encoding and decoding algorithms. In this paper, a novel approach is developed to ensure the data security issues occurred due to synchronized encoding-decoding of a BCH code and for data …transmission, a computational technique is designed by which data can be encoded and transmitted by using Field-Linear BCH code or a Ring-Linear BCH code of the same dimension, designed distance and code length. Although the Ring-Linear BCH code is preferable for encoding, on the other hand decoding of data is adept by Field-Linear BCH code. Accordingly, a computational technique of Barlekamp Massey Algorithm is utilized for the purpose. This scheme provides a quick code selection of the desired level of transmission rate and error correction capability during the communication. Thus, it also addresses the dimension issue of primitive BCH code. In addition, for the data security perspective we utilize a BCH code in round key addition and mixed column matrix steps in AES algorithm and then put on this modified AES algorithm to image encryption. The image encryption quality permits to incorporate this alteration in AES. Show more

Keywords: Primitive BCH-code, Galois ring, Galois field, generator polynomial, AES algorithm

DOI: 10.3233/JIFS-190137

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Luqman, Anam | Akram, Muhammad | Davvaz, Bijan

Article Type: Research Article

Abstract: A q -rung orthopair fuzzy model is a powerful framework for illustrating uncertainty and vagueness. This model is more practical, flexible and appropriate as compared to fuzzy, intuitionistic fuzzy and Pythagorean fuzzy models. Directed hypergraphs are utilized to execute higher-order relationships in communications and social webbing. In this research study, we design a new framework for manipulating q -rung orthopair fuzzy data by means of combinative theory of q -rung orthopair fuzzy sets and directed hypergraphs. We introduce certain new concepts, including q -rung orthopair fuzzy directed hypergraphs, dual directed hypergraphs, line graphs and coloring of q -rung orthopair fuzzy …directed hypergraphs. Further, we implement some interesting concepts of q -rung orthopair fuzzy directed hypergraphs to real life problems. Show more

Keywords: q-Rung orthopair fuzzy directed hypergraphs, dual directed hypergraphs, coloring of q-rung orthopair fuzzy directed hypergraphs, algorithms

DOI: 10.3233/JIFS-190054

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2019

Authors: Mougouei, Davoud | Powers, David M.W.

Article Type: Research Article

Abstract: Software Release Planning (SRP) is to find, for a software, a subset of the requirements with the highest value while respecting the budget. The value of a requirement however may, to various degrees, depend on selecting or ignoring other requirements. However, existing SRP models ignore either Value-Related Dependencies altogether or the strengths of those dependencies even if they consider them. This paper presents an Integer Programming model for software release planning, which considers the variances of strengths of positive and negative value-related dependencies among software requirements. To capture the imprecision associated with strengths of value-related dependencies …we have made use of algebraic structure of fuzzy graphs. We have further, contributed a scalable technique for automated identification of value-related dependencies based on user preferences for software requirements. The validity of the work is verified through simulations. Show more

Keywords: Fuzzy Graphs, Integer Programming, Value-Related Dependencies, Release Planning

DOI: 10.3233/JIFS-182810

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Vij, Sonakshi | Jain, Amita | Tayal, Devendra | Castillo, Oscar

Article Type: Research Article

Abstract: The concept of Hesitant Fuzzy Sets (HFS) came into picture where a set is created of the possible membership values that are willing to participate for contribution to the fuzzy sets. HFS has recently become very popular between researchers who are working on variants of fuzzy logic. This paper highlights the research queries related to the Scientometric analysis of HFS by studying 410 research publications from the Web of Science (v.5.31) database (from inception of Web of Science online data till 2017). This paper answers questions pertaining to the important terms and concepts for HFS, co-authorship patterns in HFS, dominating …research areas of HFS, and countries with maximum research paper contribution, co-citation patterns for first authors and bibliographical coupling for organizations. A brief outline of the citation analysis is also made in the form of a sub-section. Show more

Keywords: Fuzzy logic, hesitant fuzzy sets, HFS, Scientometric analysis

DOI: 10.3233/JIFS-179435

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Rashmanlou, Hossein | Pal, Madhumangal | Raut, Sreenanda | Mofidnakhaei, F. | Sarkar, Biswajit

Article Type: Research Article

Abstract: Theoretical concepts of graphs are highly utilized by computer science applications. Especially in research areas of computer science such as data mining, image segmentation, clustering, image capturing and networking. The intuitionistic fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that they have many applications in networks. The main purpose of this paper is to introduce some connectivity concepts in the intuitionistic fuzzy graphs. Analogous to fuzzy cutvertices and fuzzy bridges in fuzzy graphs, intuitionistic fuzzy cutvertices and intuitionistic fuzzy bridges are introduced and characterized. We also proposed the concept of gain and loss for …paths and pairs of vertices. Finally, we give an application of intuitionistic fuzzy digraphs. Show more

Keywords: Intuitionistic fuzzy digraph, gain, loss, intuitionistic fuzzy cutvertices, intuitionistic fuzzy bridge

DOI: 10.3233/JIFS-182961

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Chen, Yingyue | Chen, Yumin | Yin, Aimin

Article Type: Research Article

Abstract: Feature extraction for blind image steganalysis produces much features or high dimensional data, which bring about time consuming and even a low detection percentage. As being one of the most important phases of preprocessing, feature selection can reduce these extracted features, and improve the performance of steganalysis. Firstly, we introduce the Neighborhood Rough Sets (NRS) to the field of blind image steganalysis. Then, some concepts of feature significance and feature reduct are presented based on NRS. Furthermore, we propose a Feature Selection approach by NRS for blind image steganalysis (FSNRS). The FSNRS has the ability to delete redundant features, meanwhile …maintaining the classification accuracy of a steganalysis system. The FSNRS is a filter feature selection technique for blind image steganalysis, which filtrates extracted features depending on a positive region preserving in NRS. The compact feature subset with a shortest feature dimension for blind image steganalysis is selected. Moreover, some experiments for blind steganalysis using SVM and KNN classifiers on selected feature subset are carried out. The experimental results show that our proposed approach can obtain compact features for blind image steganalysis and the performances of classifiers on those selected features are improved. Since the FSNRS is used with an adjustable neighborhood parameter, as a result, the classification performance of selected features is better than that of original whole features in most cases. Show more

Keywords: Image steganalysis, blind steganalysis, feature selection, neighborhood rough sets, rough sets

DOI: 10.3233/JIFS-182836

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Rehmani, Sameeha | Sunitha, M.S.

Article Type: Research Article

Abstract: In this paper, the edge version of the geodesic number of a fuzzy graph is introduced and the properties satisfied are identified. A comparison between the vertex and edge version of the geodesic number of fuzzy graphs is obtained. The edge geodesic number of fuzzy trees, complete fuzzy graphs, complete bipartite fuzzy graphs and of fuzzy cycles are identified. A necessary and sufficient condition for the existence of an edge geodesic cover in a fuzzy graph is obtained. An application of edge geodesic sets in transportation systems in optimizing the number of traffic inspectors patrolling an urban road network is demonstrated. …The fuzziness in the problem helps to identify routes receiving less priority among passengers, elimination of which minimizes the loss suffered by various transport corporations due to lack of collection. Show more

Keywords: Edge geodesic cover, edge geodesic basis, edge geodesic number AMS Mathematics Subject Classification (2010): 05C72, 05C12, 05C38, 05C40, 90C35

DOI: 10.3233/JIFS-190383

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Sornam, M. | Vanitha, V.

Article Type: Research Article

Abstract: The standard backpropagation algorithm has already proven its effectiveness in most of the potential problems, but the major limitation is entrapment of local minima and slow convergence rate. To address these issues, a modified backpropagation algorithm has been proposed by adding a third term called inertia, the physical component used to accelerate the network towards the convergence without getting stuck into local minima. The Chebyshev polynomial form is a convenient method for expanding a function in a linear independent term. Inertia has been expanded using Chebyshev polynomial which is used as a third term in weight updation. The performance of …the proposed algorithm outperforms the standard backpropagation algorithm (SBP) and the backpropagation algorithm with momentum (SBPM). The proposed algorithm was tested with the standard benchmark problems such as XOR problem, parity checking problem and dataset from UCI machine learning repository such as iris flower classification, wheat classification, breast cancer detection and wine classification. Experimental results show that the addition of the third parameter called inertia in the backpropagation algorithm gave better performance and faster convergence rate compared to the SBP and SBPM. Show more

Keywords: Back propagation, chebyshev polynomial, feed forward neural network, inertia, momentum

DOI: 10.3233/JIFS-190063

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Shao, Ming-Wen | Wu, Wei-Zhi | Wang, Chang-Zhong

Article Type: Research Article

Abstract: There are mainly two classes of approaches in the studies of Formal Concept Analysis (FCA), i.e. the constructive and axiomatic approaches. In axiomatic approach, operators are interpreted by using operations in mathematical systems instead of operations in a formal context. Seeking for minimal axioms to characterize the concept generation operators is an important issue in the research of the axiomatic approach. In this paper, axiomatic characterizations of set-theoretic operators are investigated. We construct an adjoint generalized (dual) concept systems in which the pair of classical concept generation operators are represented by one set-theoretic operator, and the other operator can be …obtained from the former. Compared with the previous methods, the proposed generalized (dual) concept systems have fewer axioms and is easy to verify. Some properties of adjoint generalized (dual) concept systems are examined. Show more

Keywords: Concept lattice, galois connection, generalized concept system, set-theoretic operator

DOI: 10.3233/JIFS-182612

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Atanassov, Krassimir | Vassilev, Peter

Article Type: Research Article

Abstract: In the present paper we show that Inconsistent intuitionistic fuzzy sets, Picture fuzzy sets and Neutrosophic fuzzy sets are representable by Interval-valued intuitionistic fuzzy sets, which themselves are representable by an ordered pair of the standard Intuitionistic fuzzy sets.

Keywords: Interval-valued intuitionistic fuzzy set, Intuitionistic fuzzy set, Inconsistent intuitionistic fuzzy set, Picture fuzzy set, Neutrosophic fuzzy set

DOI: 10.3233/JIFS-179426

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Zhang, Yuanpeng | Chung, Fu-Lai | Wang, Shitong

Article Type: Research Article

Abstract: Fuzzy rules are very important in Takagi-Sugeno-Kang (TSK) fuzzy systems as they not only provide a mapping mechanism for input patterns but also make fuzzy systems interpretable. Current works further introduce rule weights to restrict/strengthen fuzzy rules for more situations. However, most of the embedded rule weights in fuzzy rules are static. In other words, the rule weights keep unchanged once they have been determined by the learning algorithms. In practical applications, it is often expected that each fuzzy rule should deduce different confidence degrees with respect to different input patterns. In this paper, a new TSK fuzzy system is …proposed, in which each fuzzy rule is empowered by an individual dynamic rule weight (DRW). DRW is basically a nonlinear function of the input pattern to reflect the confidence degree (acceptability) the fuzzy rule acting on the input pattern. Furthermore, for an input pattern, its “isolation” level can be measured by the aggregated DRW values of the fuzzy rules in the proposed fuzzy system. Specifically, the proposed fuzzy system can be used to identify outliers whose aggregated DRW values of all fuzzy rules are very small. In order to effectively embed DRW to each fuzzy rule, an analogous stacked structure consisting of a basic input-output unit and an augmenting unit is proposed. The stacked architecture is characterized by three features: (i) the augmented information from the augmenting unit can provide indirect pattern information for DRW learning; (ii) the predictive information from the augmenting unit can be differentiated from the interpretability of fuzzy rules; and (iii) the modeling performance can be improved by the stacked generalization principle which leverages the predictive information in the manifold of the input pattern space in the system approximation process. Experimental results on 16 real-life datasets demonstrate the approximation accuracy, interpretability and outlier detection ability of the proposed fuzzy system. Show more

Keywords: TSK fuzzy systems, dynamic rule weights, stacked structure, outlier detection

DOI: 10.3233/JIFS-182561

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Bashir, Zia | Rashid, Tabasam | Sałabun, Wojciech | Zafar, Sohail

Article Type: Research Article

Abstract: In this paper, the characterization of Γ -convergence for the first countable topological spaces, characterization of convergence in supremum metric in general setting and some mutual relation between these convergences are discussed. The Γ -convergence is defined as the Kuratowaski-Painlevé convergence of the endographs of the intuitionistic fuzzy sets. The supremum metric is the supremum of Hausdroff distance among the η -cuts of the intuitionistic fuzzy sets. To study these convergences is an important part of the theoretical fundamentals for intuitionistic fuzzy set theory. Some results are given as an application to variational analysis.

Keywords: Intuitionistic fuzzy sets, Pointwise convergence, Γ-convergence, Hausdroff metric, Supremum metric

DOI: 10.3233/JIFS-179429

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Zhang, Wenkai | Gao, Hengxia

Article Type: Research Article

Abstract: Hesitant fuzzy sets (HFSs) is a powerful tool in modelling and managing uncertainty of real-world decision-making problems. As a generalization of HFSs, interval-valued hesitant fuzzy sets (IVHFSs) can model preferences of decision makers with several possible interval values. Within the framework of IVHFSs, this work develops a weakly prioritized multicriteria decision analysis method for addressing problems where there exists a weakly ordered prioritization relationship over criteria. The prioritization relationship between criteria is characterized by the interval-valued hesitant fuzzy weights that are associated with criteria dependence on the satisfaction of the higher priority criteria. First, a novel prioritized scoring operator is …developed to aggregate interval-valued hesitant fuzzy information coming from simultaneous sources with different priority levels. Then, we present an operator-based decision analysis method to address multicriteria decision making problems with weakly prioritized preferences over criteria. Finally, an illustrative example of global mineral investment is provided to show the application of the proposed method. Comparison analyses with existing prioritized multicriteria decision analysis methods show that the proposed method can effectively characterize weakly ordered prioritization relationship over the criteria as well as that it can avoid information loss in eliciting the final recommendations by introducing uncertain weights. Show more

Keywords: Interval-valued hesitant fuzzy sets, weakly prioritized relationships, prioritized scoring operator, multicriteria decision analysis

DOI: 10.3233/JIFS-179427

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Aydın, Serhat | Yörükoğlu, Mehmet

Article Type: Research Article

Abstract: Ground Handling Services (GHSs) contain detailed services for airplanes and air passengers when they remain on the airport. In this paper, GHSs received by disabled air passengers and the service provider firms were focused. Neutrophosphic MULTIMOORA, a newly developed method, has been used for evaluation. Three Turkish GHSs firms are evaluated by eight criteria. The weights of evaluation criteria are determined by Analytic Hierarchy Process. Then algorithm of Neutrosophic MULTIMOORA method is applied to the problem and sensitivity analysis is presented. In the end, the conclusion is given. Contribution of this paper to the literature is using of the Neutrosophic …MULTIMOORA Method firstly for evaluation of GHSs firms. Show more

Keywords: Ground handling services, neutrosophic set, fuzzy logic, MULTIMOORA

DOI: 10.3233/JIFS-179428

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Tremante, Panayotis | Yen, Kang | Brea, Ebert

Article Type: Research Article

Abstract: The fuzzy control uses qualitative knowledge with linguistics descriptions about the operation of any process. Furthermore, Fuzzy Controller (FC) has several parameters which can be adjusted to change the performance. If this adjust is done through a “trial and error” procedure, then it will be very time-consuming and difficult to reach a good performance. Frequently, the tuning of the Membership Functions (MFs) have the most influence to improve the performance of a FC. Therefore, in this study we tune the MFs of a FC using optimization by Direct Search (DS) method, specifically the pattern search. In this sense, our goal …is to improve the performance of the system to satisfy certain conditions and propose optimization method to tune the MFs. The methodology of the optimization is simulation-based. The Objective Function (OF) is the squared error between the set point and the output of the system. The evaluation of the OF and the implementation of the fuzzy control system were performed by simulations. An explanation of the algorithmic method based on the pattern search algorithm is shown. The method proposed in this paper is illustrated with examples for the non-linear systems. The results are compared and discussed with other controllers. Show more

Keywords: Fuzzy control, membership functions, optimization, pattern search

DOI: 10.3233/JIFS-190003

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Uzun, Mert | Cebi, Selcuk

Article Type: Research Article

Abstract: Risk identification and risk assessment are the most important issues among the occupational health and safety practices. In the industry, the identification of hazards and the risk assessment are often carried out by using subjective risk assessment methods. These methods usually does not provide a perspective on the nature of the measures to be taken. In order to keep sector-specific risks under control, as important as the assessment of risks is to take effective measures against these risks and to continuously monitor the effectiveness of these measures. Therefore, the main objective of this paper is to classify protective and preventive …occupational health and safety measures implemented in the construction sector based on their efficiency by using Fuzzy Kano Model Approach. For this purpose, it is the first time, the feature classes defined by the conventional Kano Model and the Kano Model questionnaire have been reinterpreted in terms of occupational health and safety. Then, the proposed approach has been applied to classify the safety measures utilized in occupational health and safety in terms of their efficiency by using fuzzy Kano Model. According to obtain results, approximately 10% of the control measures which are effectively used at construction site are in Trusting Measure Class. The main contribution of this paper is to provide a new method for analysis of the effectiveness of the occupational health and safety measures. Show more

Keywords: Safety measures, fuzzy kano model, accident prevention, construction accidents

DOI: 10.3233/JIFS-179432

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Türkşen, Özlem

Article Type: Research Article

Abstract: Obtaining interval estimates of nonlinear model parameters is as important as point estimates of model parameters. Because the estimated value of the parameters cannot always be expressed as a single numerical quantity exactly. In this study, it is aimed to propose an interval estimation procedure for nonlinear model parameters with combining soft computing methods instead of using probabilistic assumptions. For this purpose, response and model parameters were presented as triangular fuzzy numbers (TFNs) in nonlinear regression model. The errors were defined as intervals through alpha-cut operations and minimized according to the least absolute deviation (LAD) metric. The novelty of the …study is achieving the minimization in a multi-objective framework in which the objective functions are lower and upper bound of interval type error functions. The NSGA-II (Non-dominated Sorting Genetic Algorithm-II) and the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods were used for multi-objective optimization (MOO) and multi-criteria decision making (MCDM) stages, respectively. Innovatively, in order to obtain reasonable interval estimates, predefined sized compromise solution set was composed and the fuzzy C-means (FCM) clustering algorithm was applied to the compromise set of interval estimates according to the predicted alpha-cut values. The proposed interval estimation approach is applied on a synthetic and a real data sets for application purpose. Show more

Keywords: Interval estimates of nonlinear model parameters, fuzzy nonlinear regression, fuzzy alpha-cut, NSGA-II, TOPSIS, FCM

DOI: 10.3233/JIFS-179434

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Seker, Sukran

Article Type: Research Article

Abstract: Multiple Criteria Decision Making (MCDM) methods have been widely used in literature with different extensions to handle uncertain information for years. The aim of this study is to propose an improved Complex Proportional Assessment (COPRAS) approach by integrating Interval-Valued Pythagorean Fuzzy Set (IVPFS) which is the extension of interval-valued intuitionistic fuzzy set (IVIFS) to deal with MCDM problems in the uncertain environment. It is evident from the previous studies in the literature, extension version of COPRAS method with IVPFSs is first proposed. In order to illustrate the applicability and accuracy of the proposed approach, a real-world application of selecting the …optimal fiber optical access network strategy for Arnavutkoy district in Istanbul is presented. Sensitivity analysis is applied to examine the robustness of the proposed method. A comparative analysis of the proposed method with other existing methods is also conducted. Show more

Keywords: MCDM, uncertainty, COPRAS, IVPFS

DOI: 10.3233/JIFS-179430

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Ohta, Robison | Salomon, Valerio A.P. | Silva, Messias B.

Article Type: Research Article

Abstract: A multi-criteria problem involves the consideration of two or more criteria in the prioritization of alternative solutions. The Analytic Hierarchy Process (AHP) is a leading multi-criteria method. Consistency checking is a great advantage of AHP. Since in AHP priorities come from pairwise comparisons, it is possible to check the consistency of these comparisons. However, a problem occurs when comparisons fail the consistency check. Then, the excluding options are to review some comparisons (Option 1) or to keep the comparisons (Option 2). This paper presents an AHP application in the maintenance management of an industrial plant. Industrial maintenance is not in …the core business of an organization. However, maintenance costs can account over 50% of production costs. One of the first maintenance management decisions is on the maintenance strategy. Shall maintenance anticipate the occurrence of failure? Or shall maintenance be performed after an equipment breakdown? Answering those questions with classical AHP resulted in inconsistent comparison matrices. In that case, Fuzzy AHP (FAHP) were applied, avoiding this situation. Therefore, the purpose of this paper is to present the applications of four AHP models: Classical AHP and three models of FAHP, including hesitant fuzzy sets and intuitionistic fuzzy sets. The application of Hesitant FAHP (HFAHP) and Intuitionistic FAHP (IFAHP) are the novelty of this paper. The four AHP models were also applied in the same case of maintenance management of an industrial plant. Results were very similar, but experts could express their preferred model. Show more

Keywords: Analytic hierarchy process, hesitant fuzzy sets, intuitionistic fuzzy sets, maintenance management

DOI: 10.3233/JIFS-179433

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Sulaiman, Muhammad | Samiullah, Ismat | Hamdi, A. | Hussain, Zubair

Article Type: Research Article

Abstract: In this paper, we have used a novel initialization strategy to improve Whale optimization algorithm (WOA) which is named as The Improved Whale Optimization Algorithm (IWOA). To evaluate the capability of the algorithm in terms of efficiency and performance we have implemented it to solve thermal economic multi-objective optimization problems of Plate Fin Heat Exchanger (PFHE). We have investigated the design problem with a single-objective as well as multi-objectives. In single-objective we have minimized the total cost and maximized the effectiveness of PFHE. In multi-objective, we have combined the total cost and effectiveness, with the help of design weights and …a penalty parameter. The sensitivity of IWOA is checked towards the change in population sizes and the target prey numbers. The algorithm was stable in calculating the best values, but was variative in number of functions evaluations. The performance of IWOA is compared with Genetic Algorithm (GA), Elitist-Jaya Algorithm (EJA), and modified-TLBO (Teaching Learning Based Optimization). Which show that IWOA has significantly improved the results. The suggested algorithm has less parameters to be set by designers. It converges to the required results quickly and is easy to implement. Similarly, all the experiments suggested that IWOA is applicable to design problems with complex objectives and highly non-linear constraints. Show more

Keywords: Design Engineering Problems, Whale Optimization Algorithm (WOA), Plate Fin Heat Exchanger (PFHE), Constrained Optimization

DOI: 10.3233/JIFS-190081

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Moraes, Ronei Marcosde | Soares, Elaine Anitade Melo Gomes | Machado, Lilianedos Santos

Article Type: Research Article

Abstract: Classifiers based on Gamma statistical distribution can be found in the scientific literature, but they assume the collected data doesn’t present any errors. However, in some cases, information precision can not be guaranteed, then the fuzzy approach is convenient. Several methods found in the literature are not able to ponder the specific contribution of each class and/or feature for the classification tasks. This paper presents a proposal of a new classifier named Doubled Weighted Fuzzy Gamma Naive Bayes network (DW-FGamNB). This new classifier uses two types of weights in order to allow users to ponder the real contribution of each …class and feature in the classification task. The theoretical development is presented, as well as results of its application on simulated multidimensional data using Gamma statistical distribution. A comparison among DW-FGamNB, Fuzzy Gamma Naive Bayes classifier, classical Gamma Naive Bayes classifier, Naive Bayes classifier, DecionTree-Naive Bayes, Decision Tree C4.5, Logistic Regression, Multilayer Perceptron Neural Network, Adaboost-M1, Radial Basis Function Network and Random Forest was performed. The results obtained showed that the DW-FGamNB produced the best performance, according to the Overall Accuracy Index, Kappa and Tau Coefficients, and diagnostic tests. Show more

Keywords: Gamma statistical distribution, fuzzy classification, fuzzy statistics, double weighted naive bayes

DOI: 10.3233/JIFS-179431

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Xiao, Fuyuan | Zhang, Zili | Abawajy, Jemal

Article Type: Research Article

Abstract:  A well-managed time-constrained workflow scheduling is needed for improving system performance and end user satisfaction. Meanwhile, the intrinsic uncertainty in dynamic systems increases the difficulties of scheduling problem. Therefore, it is a great challenge to improve performance and optimize several objectives simultaneously. To address these issues, a novel workflow scheduling method for distributed systems based on TOPSIS method with fuzzy set is proposed in this paper. The new method can minimize the makespan of the workflow application under uncertain environment. Finally, a numerical example is provided to demonstrate the efficiency of the proposed method.

Keywords: Workflow scheduling, Triangular fuzzy numbers, TOPSIS, Distributed systems

DOI: 10.3233/JIFS-190483

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Shi, Fu-Gui | Fan, Cao-Zan

Article Type: Research Article

Abstract: In this paper, it is shown that an L -fuzzy soft set on X with a set E of parameters can be regarded as an L X -fuzzy set on E , and it can also be regarded as an L E -fuzzy set on X . Moreover an L E -fuzzy set on X can also be regarded as an L -fuzzy sets on E  × X . In particular, a soft set on X with a set E of parameters actually can be regarded as a 2 E …-fuzzy set or a crisp subset of E  × X . This shows that the concept of (fuzzy) soft set is redundant. Further it is shown that the notions of soft groups, soft rings and fuzzy soft semigroups are respectively special cases of the corresponding L -fuzzy groups, L -fuzzy rings and L -fuzzy semigroups. Therefore, theoretical workers should stop working in these restrictive and complicated programs, while applied workers should transfer the need or appropriateness of (fuzzy) soft set notions to lattice-valued fuzzy sets or fuzzy sets of type 2. Show more

Keywords: L-fuzzy set, L-fuzzy soft set, soft set, fuzzy set of type 2, complete lattice isomorphism

DOI: 10.3233/JIFS-182828

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Tehrim, Syeda Tayyba | Riaz, Muhammad

Article Type: Research Article

Abstract: In this paper, we bring out the idea of bipolar neutrosophic soft topology based on bipolar neutrosophic soft set (BNS-set). We study the properties of classical topology under bipolar neutrosophic soft (BNS) vagueness. The BNS-topology is the generalization of the fuzzy topology. We discuss certain properties of BNS-topology including, BNS-closure, BNS-interior, BNS-exterior and BNS-frontier by utilizing BNS-points. We also study the concept of BNS-subspace, BNS-neighborhoods and BNS-base for BNS-topology with the help of detailed examples and theorems. Furthermore, we propose: Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method under BNS-topological environment to deal with similarities in …medical diagnosis. We see the importance of BNS-topology in multi criteria group decision making (MCGDM) as well. We present a numerical example with real background to demonstrate the validity of our model. Finally, we make a method-based and set-based comparison analysis of proposed method with some existing methods. Compared with existing MCGDM models, this study provides a flexible framework to form an approximate decision model to real-world MCGDM problems. Show more

Keywords: BNS-topology, BNS-topological properties, BNS-TOPSIS, MCGDM, medical diagnosis

DOI: 10.3233/JIFS-190668

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2019

Authors: Tao, Zhifu | Liu, Xi | Zhou, Ligang | Chen, Huayou

Article Type: Research Article

Abstract: Z-numbers contain both of the cognitive information and the reliability of information. Since there are many types of cognitive information, by considering the reliability of these information, decision making with hybrid Z-information would be a practical issue, which has merely been considered. The aim of this paper is to introduce a multi-attribute decision making (MADM) with hybrid Z-information based on ranking aggregation method. By using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, single rankings of alternatives under attributes are firstly produced. Then, final ranking(s) of alternatives with the lowest disagreement among single rankings could …be derived according to ranking aggregation. As a result, a MADM with hybrid Z-information is transformed to be a ranking aggregation problem. The advantage of the developed method is that no algebra structures of hybrid Z-information is needed, so complex calculating process is avoided. In this paper, the mathematical structure of the case that MADM with hybrid Z-numbers is clear. Besides, the combination of ranking aggregation method and studies on Z-numbers could simplify the processing of hybrid Z-numbers. Finally, an example of supplier selection in green supply chain environment is introduced to illustrate the feasibility and validity of the developed model. Show more

Keywords: Multi-attribute decision making, hybrid Z-information, rank aggregation, supplier selection, order relation

DOI: 10.3233/JIFS-190344

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Fan, Jianping | Liu, Jie | Wu, Meiqin

Article Type: Research Article

Abstract: Cross-efficiency assessment method is a useful tool for assessing the relative performance of decision-making units (DMUs). It is generally assumed that decision makers (DMs) are completely rational in the cross-efficiency model, and DMs’ risk attitude has not been considered important in the evaluation process. When the self-evaluation score of the DMU is optimal, the input and output weights are non-unique, resulting in non-unique cross-efficiency score, which affects the ranking result. The relative importance of DMUs is ignored when aggregating cross-efficiency scores. in view of the above problems, a cross-efficiency method based on prospect theory is proposed to capture the bounded …rational psychological behavior of risk DMs. This method considers all multiple optimal solutions and constructs interval cross-efficiency. The credibility of each cross-efficiency score is obtained based on the D-S evidence theory, and the weight of each DMU is obtained by using the Dempster rule. DMUs are ranked by calculating the prospect value. The validity and feasibility of the proposed method and the how does the risk preference of DMs characterized by parameters α , β , λ affect the evaluation results are verified by an illustrative example. Show more

Keywords: Data envelopment analysis, cross-efficiency, interval number, dempster-shafer theory, prospect theory

DOI: 10.3233/JIFS-190450

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Wang, Xiao | Ning, Yufu

Article Type: Research Article

Abstract: Uncertain delay differential equations are a type of differential equations driven by a Liu process. So far, it has been proved that uncertain delay differential equation has a unique solution in the finite domain, in which its coefficients satisfy the global Lipschitz continuity. This paper continues to focus on the existence and uniqueness of the solutions of uncertain delay differential equations on the infinite domain. Meanwhile, a new existence and uniqueness theorem for uncertain delay differential equations under one-sided local Lipschitz condition and linear growth condition is deduced.

Keywords: Uncertain delay differential equation, existence and uniqueness, one-sided local Lipschitz condition, linear growth condition, infinite domain

DOI: 10.3233/JIFS-190264

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Mohammed, Shehu Shagari | Azam, Akbar

Article Type: Research Article

Abstract:  In this paper, the notion of soft set-valued mappings and E -soft fixed points are introduced. These ideas are used to establish some analogues of classical fixed point theorems in the literature. Some Examples are given to support the hypotheses of the theorems. A few graphical and tabular illustrations are also provided so as to visualize the novel concepts pictorially. Moreover, as an application of one of the presented results, an existence condition for a solution of nonlinear discrete-type delay differential equation is provided.

Keywords: soft set, soft set-valued mapping, E-soft fixed point, delay differential equation 2010 Mathematics Subject Classification: 46S40, 47H10, 54H25.

DOI: 10.3233/JIFS-190126

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: El-Saady, Kamal | Temraz, Ayat A.

Article Type: Research Article

Abstract: In this paper we consider the category M -FQMod of M -fuzzy (left) Q -modules over a given quantale Q . We introduce and investigate the notion of M -fuzzy Q -submodule of a left Q -module. Also, the notions of M -fuzzy module nuclei and conuclei on a left Q -module are defined, and the elementary properties of both are studied. The relationships between such notions and M -fuzzy Q -submodule are discussed. Finally, the relationship between the category of M -fuzzy Q -modules and the category of (L , M )-quasi-fuzzy topological …spaces is discussed. Show more

Keywords: Quantale, semi quantale, left Q-module, module nucleus and module conucleus 2000 AMS Classification: 06A06, 54A10, 54A40

DOI: 10.3233/JIFS-190073

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Jing, Li | Yulin, Zhang

Article Type: Research Article

Abstract: Interval fuzzy preference relations (IFPRs) have been widely adopted in describing vagueness and uncertainty in real-life decision problems. Different methods have been applied in aggregating decision makers’ (DMs’) IFPRs. Nevertheless, the objective weights of DMs are often neglected in the group decision literature. Besides, the commonly methods used in aggregating decision makers’ (DMs’) IFPRs may make the final result too average. This paper investigates the plant growth simulation algorithm (PGSA) to aggregate interval fuzzy preference relations (IFPRs) and then derives the objective weights of decision makers (DMs) based on the deviation measure method. Next, the weighted aggregation IFPR is obtained …by PGSA and the alternatives are ranked based on the continuous ordered weighted averaging (COWA) operator. The new aggregation method creatively converts the elements of IFPRs into two-dimensional coordinates and the ideal IFPR can be aggregated by PGSA based on the minimum Euclidean distance model. Then the weight of each DM can be derived according to the Euclidean distance between the individual IFPR and ideal IFPR based on the deviation measure method. Finally, a weighted aggregated IFPR can be obtained by PGSA and the ranking of alternatives is obtained by the COWA operator. Numerical examples are given to verify the efficiency and superiority of the method. Show more

Keywords: Weights of decision makers (DMs), interval fuzzy preference relations (IFPRs), deviation measure method, the minimum Euclidean distance model, plant growth simulation algorithm (PGSA)

DOI: 10.3233/JIFS-190410

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Wu, Peng | Li, Hongyan | Zhou, Ligang | Chen, Huayou

Article Type: Research Article

Abstract: Consistency and the priority vector are two important issues in preference relations. As one of preference relations, multiplicative trapezoidal fuzzy preference relation (MTFPR) is an effective form of vague and imprecise information when decision maker (DM) express his/her opinions by comparing alternatives or criteria with each other in group decision making (GDM). Therefore, it is meaningful to discuss the consistency and the method for deriving priority vector of MTFPRs. In this paper, we define multiplicative consistency of MTFPRs and investigate the necessary and sufficient conditions of multiplicative consistent MTFPRs. Some properties of multiplicative consistent MTFPRs are studied in detail. Based …on the necessary and sufficient conditions of multiplicative consistent MTFPRs, two consistent measurement matrices (CMMs) are developed to define an acceptably multiplicative consistent MTFPR. A logarithmic least square model is further constructed for deriving a normalized trapezoidal fuzzy priority vector from a MTFPR. Three numerical examples including a GDM problem are analyzed to demonstrate the validity of the proposed models. Show more

Keywords: Group decision making, multiplicative trapezoidal fuzzy preference relations, multiplicative consistency, logarithmic least square priority model

DOI: 10.3233/JIFS-190846

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2019

Authors: Liu, Xiaoyong | Yun, Zhonghua | Yang, Hang | Zhang, Qiang

Article Type: Research Article

Abstract: In this paper, a novel method for fault detection based on an adaptive interval regression model characterized by the upper regression model (URM) and lower regression model (LRM) has been proposed. Applying the proposed method, a confidence band for the measured data, derived in the normal operating conditions of a system, is constructed.The method combines the superiorities of model sparse representation and computational efficiency of linear programming support vector regression (LP-SVR) with some ideas from L 1 -norm on approximation errors. First, the upper and lower L 1 -norms with respect to upper bound approximation error are considered, and the …both norms subject to respective constraints are integrated into LP-SVR to form new upper and lower optimization problems, respectively. Following that, optimization problem corresponding to URM and LRM are solved by linear programming and interval regression model is thus constructed to judge whether the fault occurs or not. The proposed method returns an interval output as opposed to a point output. Finally, the efficacy of this method is demonstrated by applying it on the benchmark Tennessee Eastman problem, and has been compared with conventional techniques such as principal component analysis (PCA), dynamic-PCA (DPCA) and One-Class Support Vector Machine(1-class SVM). It is shown that the proposed method is superior to those approaches in terms of performance measure of detection latency. Show more

Keywords: Fault detection, LP-SVR, L1-Norm minimization, linear programming, interval regression model

DOI: 10.3233/JIFS-190176

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Wang, Lan | Pang, Bin

Article Type: Research Article

Abstract: In this paper, we mainly focus on the relationship between (L , M )-fuzzy closure systems and (L , M )-fuzzy convex structures as well as the relationship between (L , M )-fuzzy closure systems and (L , M )-fuzzy cotopologies. Firstly, we show that there is an adjunction between the category LMFC of (L , M )-fuzzy convex spaces and the category LMFS of (L , M )-fuzzy closure spaces, and there is also an adjunction between the category LMFT of (L , M )-fuzzy cotopological spaces and LMFS . In particular, the categories LMFC …and LMFT are both coreflective subcategories of LMFS . Secondly, we prove that there is an adjunction between the category ELFC of extensional L -fuzzy convex spaces and the category LFC of L -fuzzy convex spaces, and there is also an adjunction between the category ELFT of extensional L -fuzzy cotopological spaces and the category LFT of (L , M )-fuzzy cotopological spaces. Specially, ELFC is a coreflective subcategory of LFC and ELFT is a coreflective subcategory of LFT . Show more

Keywords: (L, M)-fuzzy closure system, (L, M)-fuzzy convex structure, (L, M)-fuzzy cotopology, coreflective subcategory

DOI: 10.3233/JIFS-182963

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Qu, Guohua | Li, Tianjiao | Qu, Weihua | Xu, Ling | Ma, Xiaolong

Article Type: Research Article

Abstract: Interval-value dual hesitant fuzzy set, first proposed by Ju et al. (Interval-valued dual hesitant fuzzy aggregation operators and their applications to multiple attribute decision making, 1203–1218, 2014). Multiple attribute decision making with dual hesitant fuzzy information is a new research topic since dual hesitant fuzzy set was firstly proposed, it has been widely studied in the fuzzy decision making literature. As a new generalization of fuzzy sets, interval-value dual hesitant fuzzy set (IVDHF) This article develops a multi-attribute decision making method considering the regret value theory and group satisfaction for the interval-value dual hesitant fuzzy element and incomplete weight information. …Considering that decision makers have different level of the degree of evaluation, firstly, based on the score function and the accuracy function of the interval-valued hesitant fuzzy element, the deviation function of the interval-valued hesitant fuzzy set is defined. On this basis, a new group satisfaction is proposed. And then, for the situation where the information of attribute weight is incompletely known and completely unknown, some optimization models of attribute weight are established by using the new group satisfaction degree, and then the attribute weight can be determined. Finally, a real example of investment alternative evaluation is carried out to validate the implementation of the proposed approach. Show more

Keywords: Interval-valued dual hesitant fuzzy set, group satisfaction degree, regret theory, stochastic multiple attribute decision making

DOI: 10.3233/JIFS-182634

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Farias, Missilene da S. | Mendes, Willians R. | de Araújo, Fábio Meneghetti U.

Article Type: Research Article

Abstract: Many researches use T-S fuzzy models to accurately represent nonlinear dynamic systems. However, T-S fuzzy makes the implementation of fuzzy controller more complex as system order and nonlinearities increase. Thus, the present work is aimed to overcome these limitations by using an Interval Type-2 Fuzzy Rule-Based System in which the membership functions and the number of rules can be freely chosen simplifying the implementation of the technique. To this end, it is established a direct state feedback control with reference tracking to generate the nonlinear control action using parallel distributed compensation techniques with no need to include T-S fuzzy models …to describe the dynamic system. The proposed strategy is applied to a synchronous generator and also to a magnetic levitation system. From the results, it was verified that IT2FRBSs are able to stabilize the systems analyzed at different equilibrium points with higher performance and less settling times, given the uncertainties in the linearized model. In fact, the IT2FRBS proved to be a proper way to accomplish this task, because fuzzy logic control itself does not depend on an accurate model. Show more

Keywords: Type-2 fuzzy, nonlinear systems, state feedback, reference tracking

DOI: 10.3233/JIFS-190537

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2019

Authors: Guo, Zixue | Sun, Fangfang

Article Type: Research Article

Abstract: In the multi-attribute decision-making problems, uncertain information can be well-represented by single-valued neutrosophic linguistic sets (SVNLSs); Decision makers’ different risk attitudes toward gains and losses can be solved by prospect theory (PT). Based on both, a novel integrated fuzzy decision method is proposed which combines SVNLS and PT (SVNLS-PT). In this method, we extend linguistic scale function to adapt the single-valued neutrosophic linguistic environment. Based on the extended linguistic scale, we introduce the operational laws, some aggregation operators and the distance calculating method of SVNLS. Besides, the PT is employed to rank the alternatives. In order to reflect both the …subjective considerations of decision makers and the objective information, weights of attributes are combined by objective weights and subjective weights which objective weights are obtained by mean-squared deviation method and subjective weights by establishing the liner programing model. Finally, a case study concerning investment project of Internet of Vehicles is provided to illustrate the applicability of the proposed method. Show more

Keywords: Single-valued neutrosophic linguistic set, prospect theory, combined weight, multi-attribute decision making

DOI: 10.3233/JIFS-190509

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Imran, Muhammad | Siddiqui, Muhammad Kamran | Baig, Abdul Qudair | Khalid, Waqas | Shaker, Hani

Article Type: Research Article

Abstract: Graph theory is a fundamental and energetic tool for designing and modeling a graph/network. There are certain topological indices based on degree, distance and eccentricity, etc. The topological indices essentially relate certain physio-concoction properties and bio-activity to the corresponding synthetic and atomic structure. In this paper, our aim is to figure out degree-based topological indices mainly atom-bond connectivity (ABC ), geometric-arithmetic (GA ), ABC 4 and GA 5 indices for cellular neural network (CNN) and give closed results of these indices for cellular neural network. Moreover, we also compute general Randi c ´ …index R α of CNN for α = { 1 , - 1 , 1 2 , - 1 2 } only and give analytical closed form results. A 3D graph analysis for comparison of indices is also given. Show more

Keywords: Molecular descriptor, cellular neural network, atom bond connectivity index, geometric arithmetic index, general Randić index

DOI: 10.3233/JIFS-181813

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Yogashanthi, T. | Mohanaselvi, S. | Ganesan, K.

Article Type: Research Article

Abstract:  In this paper a new centroid based ranking grade for generalized intuitionistic fuzzy numbers is proposed. The centroid point of membership function and non membership function of generalized intuitionistic fuzzy numbers in term of its parametric form is used for grading. The parametric representation of generalized intuitionistic fuzzy numbers involves left fuzziness index, right fuzziness index and modal value of membership and non membership functions. To reveal the performance of the proposed ranking grade, a comparison study has been made over the existing methods. Furthermore the proposed ranking method has been used for estimating the minimum total elapsed time to …a flow shop scheduling problem involving generalized intuitionistic fuzzy number. An improved result for flow shop scheduling problem has been attained using the proposed ranking grade and has been illustrated through an example. Show more

Keywords: Fuzzy set, generalized intuitionistic fuzzy numbers, centroid point, ranking grade, flow shop scheduling problem

DOI: 10.3233/JIFS-190395

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Ali, Abbas | Rehman, Noor | Jang, Sun Young | Park, Choonkil

Article Type: Research Article

Abstract:  The notions of fuzzy upward β -covering, the fuzzy upward β -neighborhood, upward β -neighborhood and fuzzy complement β -neighborhood are introduced and several related properties are studied. Furthermore, multigranulation optimistic/pessimistic fuzzy rough sets based on fuzzy upward β -covering are initiated and their fundamental properties are investigated. We also find the upward β -neighborhood in the fuzzy upward covering approximation space and present the optimistic/pessimistic multigranulation rough sets to further enrich the presented notions. The medicine selection via fuzzy upward β -covering rough sets in medical diagnosis is another main contribution of the present work. It is also explored …that which medicine can be prescribed for which particular symtom(s) and which disease. Show more

Keywords: Fuzzy preference relation, fuzzy rough set, β-covering rough sets

DOI: 10.3233/JIFS-190447

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-22, 2019

Authors: Cheng, Qiang | Wang, Hao | Liu, Zhifeng | Zhang, Caixia | Sun, Dongyang | Qi, Baobao

Article Type: Research Article

Abstract: Reliability allocation is one of the most important factors to consider when determining the reliability and competitiveness of a product. The feasibility-of-objectives (FOO) technique has become the current standard for assessing reliability designs for military mechanical–electrical systems. However, the FOO method has several drawbacks: For instance, it requires that the value of reliability allocation factors is single linguistic variables, and it does not consider the ordered weight of reliability allocation factors, but simply multiplies the ISPE (Complexity (I), State of Art (S), Performance Time (P), and Environment (E)) values one by one. This can lead to erroneous results. To address …these issues, this paper combines the fuzzy allocation method with the maximum entropy ordered weighted averaging method (ME-OWA) to achieve a flexible allocation of system reliability. To verify the effectiveness of the proposed method, the CNC machine tool is taken as an example. The FOO method and the fuzzy allocation method and the proposed method were used to assign reliability to the eight subsystems of a CNC machine tool, and the results were compared to draw conclusions: The proposed method is more flexible and accurate for reliability allocation. Show more

Keywords: Reliability allocation, feasibility-of-objectives technique (FOO), the maximum entropy ordered weighted averaging method (ME-OWA), CNC machine tools

DOI: 10.3233/JIFS-190376

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Liu, Peide | Shen, Mengjiao

Article Type: Research Article

Abstract: As the extension of intuitionistic fuzzy numbers (IFNs), linguistic intuitionistic fuzzy numbers (LIFNs) is proposed. LIFNs are expressed by linguistic variables and take the membership degree (MD) and non-membership degree (NMD) into consideration. The MD and NMD of LIFNs can easier describe complex and fuzzy information in multiple attribute decision-making (MADM) problems. The TODIM method based on prospect theory can reflect the psychological factors of the decision makers (DMs). However, existing TODIM methods neither handle the decision-making problems under linguistic intuitionistic environment nor consider interrelations among multiple attributes. Based on these problems, in this paper, combining the fuzzy measure with …the TODIM method, an extended Choquet-TODIM method is proposed to process the MADM problems. The extended Choquet-TODIM method considers the interrelationship of multiple attributes and the bounded rationality of DMs. Firstly, the relative theories of LIFNs, the classical TODIM method and λ -fuzzy measures are briefly reviewed. Secondly, the TODIM method is extended to linguistic intuitionistic fuzzy environment and C-TODIM method of LIFNs is proposed. Then λ -fuzzy measure is extended to the classical TODIM method and a model of determining fuzzy measures is proposed. The proposed method gives the new solution to calculate the fuzzy measures and address the MADM problems with interrelationship among different attributes. Lastly, two numerical examples are used to compare with two existing methods and explain the effectiveness and superiority of this method. Show more

Keywords: Linguistic intuitionistic fuzzy numbers, TODIM method, fuzzy measures, multiple attribute decision making

DOI: 10.3233/JIFS-182554

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Bush, Idoko John | Abiyev, Rahib | Arslan, Murat

Article Type: Research Article

Abstract: In this study, we propose a vision-based mouse controller capable of controlling objects from a distant location via hand gestures. The proposed hybrid model constitutes hand detection, prediction of hand states and direction and finally, with the aid of deep learning algorithm, we systematically control hand gestures to reposition objects on computer screen. This hybrid system is explicitly designed to control mouse on computer screen during formal presentation. Random movement of hand from up to down and right to left move the mouse pointer and sends signal to the system utilizing states of the hand. Here, close hand places the …mouse button on active mode while open hand releases the button. The proposed hybrid model is made up of two modules: Single Shot Multi Box Detection (SSD) structure utilized to detect hand while Convolutional Neural Network (CNN) is utilized for prediction. For comparative purposes, we performed similar experiment where SSD is used for hand detection while Radial Basis Function Network (RBFN) is used for hand states prediction. In the comparative results of hand states prediction, SSD+CNN greatly outperformed SSD+RBFN. The proposed hybrid model is vision-based hence, it does not require additional hardware to perform its task. Overall performance of the framework depicts that the system is accurate and robust. Show more

Keywords: Hand gesture, convolutional neural network, radial basis function network, computer vision, deep learning

DOI: 10.3233/JIFS-190353

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Li, Zhiming

Article Type: Research Article

Abstract: Uncertain differential equation has become an important tool to deal with uncertain dynamic systems such as finance, control and medical fields. The paper aims to study the problem of estimating unknown parameters in uncertain differential equations (UDEs). Least-square method is introduced to estimate unknown parameters of a class of simple UDEs. Further, two least-square estimators of a simple UDE are obtained. The simulation results show that the proposed method is feasible for estimating unknown parameters of some UDEs.

Keywords: Uncertain measure, uncertain differential equation, parameter estimation, least-square method

DOI: 10.3233/JIFS-190521

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Mao, Wenxin | Wang, Wenping | Sun, Huifang

Article Type: Research Article

Abstract: The increasingly complex decision environments determine the classical grey number is insufficient to tackle the asymmetrical grey information distribution in multi-attribute group decision making, and there usually exits causal interdependency between attributes, motivated by this a grey possibility based hybrid decision method is proposed in this paper. First, the possibility function is used to characterize the asymmetrical value distribution information of grey number. The novel measure functions including the ranking method, grey orthocenter distance and similarity degree of grey number are constructed. On this basis, the optimization model for aggregating group grey information is designed based on the two goals …which are the minimal distances and higher similarity between individual grey information. The grey possibility based hybrid decision method is established by integrating the decision making trial and evaluation laboratory and the interactive multi-attribute decision method (TODIM) with considering the bounded rationality behavior of decision maker under high-type grey decision environment, where the causal interdependencies between attributes are overcome. Finally, the proposed method is applied to a strategy selection problem of Chinese smart phone manufacturer, and the sensitivity and comparative analysis are carried out to verify its robustness and credibility. Show more

Keywords: Grey number, possibility function, multi-attribute decision making, TODIM, DEMATEL

DOI: 10.3233/JIFS-190463

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Chen, Jin | Meng, Sun | Zhou, Wei

Article Type: Research Article

Abstract: In today’s society, many decision-making problems cannot be merely solved based on quantitative data. Even though some issues are able to be addressed by quantitative data, researchers may face the difficulty of obtaining accurate and sufficient numbers. Some qualitative evaluations given by experts or decision makers are usually linguistic expressions. Therefore, fuzzy linguistic research has been broadly studied to address the above issues. This research has also been attracting increasing attention from researchers and decision makers in the world. It is believed that analyzing the status quo and emerging trends in this research area is of great necessity, especially for …the beginners who are interested in fuzzy linguistic research. To do so, this paper provides the mapping knowledge domain of fuzzy linguistic research based on 648 papers on Web of Science from 1975 to 2018 by using CiteSpace which is an effective tool for scientometric studies. The visualization analyses of cited reference clusters, collaborations networks, author co-citation networks, burst detection and time zone view are presented in this study to show the research streams and the papers that made significant theoretical contributions. Also, the active counties, institutions, journals and authors in this research area are analyzed in detail. Besides, the specific hot spots and emerging trends can be known. There are two contributions in this study. Firstly, we give a comprehensive investigation about the status quo and emerging trends of fuzzy linguistic research in the recent 43 years. Secondly, we make the development of fuzzy linguistic research easier and direct to learn for beginners. Show more

Keywords: Fuzzy logic, linguistics, decision making, CiteSpace, scientometric

DOI: 10.3233/JIFS-182737

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Qu, Weibin | Yan, Hongyan | Zhu, Yuanguo | Chen, Xin

Article Type: Research Article

Abstract: The uncertainty theory is a branch of mathematics for studying subjective uncertainty phenomenon, and its role in subjective uncertain problems helps people make better decisions. But in real life, there is not a standard method to deal with multiple experts’ data problem. A simple method is to average all experts’ data to get a result. The other is to use the Delphi method to collect data many times and then get a normal result. This paper gives two new methods to handle this problem through conditional distributions. Compared to traditional method, they do not require all experts’ data from the …beginning and the result obtained by these methods can be updated easily when new expert’s data is given. Show more

Keywords: Uncertain statistics, multiple experts model, conditional uncertainty distribution, Delphi

DOI: 10.3233/JIFS-190553

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Shang, Yu | Li, Zhe | Wang, Zhanlin | Yang, Sifeng | Zhou, Jinglun

Article Type: Research Article

Abstract: Most recently, uncertain and fuzzy factors appear frequently in group decision making (GDM) researches. A more realistic approach may be to use scientometric tools for carrying out the systematic review to disclose the fast-growing uncertain and fuzzy GDM methods. The aim of this paper is to show a comprehensive presentation of the state of these approaches. To achieve this goal, a systematic literature review of researching articles, which have been published in Science Citation Index (SCI) journals since 1965, is proposed. And this study mainly uses the software of CiteSpace which has been frequently used in data visualization field due …to its universality in order to map the main trends in this subject. This work considers the leading categories, journals, authors and references, and the results indicate that the GDM research would continue to flourish. Additionally, some possible approaches that could improve the current fuzzy GDM methods are presented. Show more

Keywords: Group decision making (GDM), bibliometric method, citespace, citation burst

DOI: 10.3233/JIFS-190631

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Kuo, R.J. | Kuo, R.J. | Cheng, W.C. | Lien, W.C. | Yang, T.J.

Article Type: Research Article

Abstract: Taiwan is an endemic area for chronic hepatitis disease. Since the early 1980’s, liver cancer has become the first cancer mortality causes among other cancers in Taiwan. Besides, liver cirrhosis and chronic liver diseases are the sixth rank and seventh rank in the causes of death, respectively. This is a serious disease affecting people’s health and it brings a lot of medical cost as well. This study develops a medical cost forecasting model for the acute hepatitis patients in the emergency room. In order to consider the uncertainty and hesitation in the human being’s thinking, this study employs the intuitionistic …fuzzy logic (IFL) since it considers membership, non-membership, and hesitation values simultaneously. The proposed model combines the intuitionistic fuzzy neural network (IFNN) with Gaussian membership function and Yager-Generating function to enhance the performance of FNN. Furthermore, a back-propagation learning algorithm and genetic algorithm (GA) are applied in order to optimize the parameters and weights of the proposed IFNN. The proposed IFNN is applied to solve ten benchmark datasets including the nonlinear control and prediction problems. The computational results showed that the GA-IFNN is more efficient than conventional algorithms, such as an artificial neural network (ANN), a fuzzy neural network (FNN), and a support vector regression (SVR). In the real-world problem, the proposed method can really support physicians in planning medical resources and make a good decision to make the most efficient use of limited resources. Show more

Keywords: Fuzzy neural network, intuitionistic fuzzy logic, intuitionistic fuzzy neural network, continuous genetic algorithm, medical cost forecasting

DOI: 10.3233/JIFS-190554

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Liu, Jinjin | Ke, Hua

Article Type: Research Article

Abstract: With the rapid-developing social media, firms increasingly employ social media for different organizational purposes, including operations, marketing and innovation management. Meanwhile, a social media retailing channel as the outcome of integrating social media with online retailing has received increasing attention in a variety of industries and academic fields. Moreover, products update is getting faster and faster with rapid-developing technologies, which usually leads to more indeterminate information on demands and costs, thus the indeterminacy should be taken into account in pricing decisions. Based on this, we explore the impact of introducing this new channel on a traditional distribution channel under uncertain …environment. Specifically, we construct two uncertain bilevel programming models under different channel structures, in which the demand of the social media channel is characterized as sensitive to the intensity of the social relationship. We find introducing the social media channel may either increase or decrease wholesale price and the traditional retailer’s retail price, depending on the expected value of the intensity of the social relationship. When the social media channel is introduced, equilibrium prices will increase with the intensity of social relationship, namely, a stronger social relationship leads to a higher retail price not only in the social media channel but also in the tradition channel. A series of numerical experiments show that a rise in the uncertain degree of the intensity of the social relationship will raise the manufacturer’s expected profit, but has no impact on equilibrium prices and the retailer’s expected profit. Show more

Keywords: Social media retailing, social relationship, dual channel, pricing decision, uncertainty theory

DOI: 10.3233/JIFS-190595

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Meng, Qiqi | Liu, Xinwang | Song, Yu | Wang, Weizhong

Article Type: Research Article

Abstract: Different from the traditional supply chain, there are more uncertainty in the supply chain of social commerce (SCOSC), which brings new risk. As a fundamental stage in the supply chain risk management (SCRM), risk assessment can effectively control risks in supply chain. To address risk preference of decision makers (DMs) and the criteria ambiguity, this paper proposes an extended generalized TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method within interval type-2 fuzzy sets (IT2FSs) to evaluate the risk of the SCOSC. First, the generalized TODIM is extended with two different value functions based on two types …of criteria, cost and benefit, and the alternatives are ranked according to the distance to the ideal solution and the negative-ideal solution. Second, the IT2FSs is applied to deal with the linguistics ambiguity with the generalized TODIM method. Furthermore, the risk assessment of SCOSC based on the extended generalized TODIM within IT2FSs is proposed. Finally, a case of the risk assessment in SCOSC is presented to validate the effectiveness of the proposed method. Show more

Keywords: Supply chain of social e-commerce, risk assessment, generalized TODIM, interval type-2 fuzzy set

DOI: 10.3233/JIFS-190061

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Rahman, Khaista | Abdullah, Saleem

Article Type: Research Article

Abstract: The concept of interval-valued Pythagorean fuzzy (IVPF) sets is capable of handling imprecise and ambiguous information and managing complex uncertainty in real-world applications. The focus of our this paper is to introduce some generalized operators, such as the generalized interval-valued Pythagorean fuzzy Einstein weighted averaging (abbreviated as GIVPFEWA) operator, the generalized interval-valued Pythagorean fuzzy Einstein ordered weighted averaging (abbreviated as GIVPFEOWA) operator, and the generalized interval-valued Pythagorean fuzzy Einstein hybrid averaging (abbreviated as GIVPFEHA) operator along with their some general properties, such as idempotency, commutativity, monotonicity and boundedness. Furthermore, the method for multiple attribute group decision making problems based on …these operators was developed, and the operational processes were illustrated in detail. The main advantage of using the proposed methods and operators is that these operators and methods give a more complete view of the problem to the decision makers. These methods provide more general, more accurate and precise results as compared to the existing methods. Therefore these methods play a vital role in real world problems. Finally the proposed operators have been applied to decision-making problems to show the validity, practicality and effectiveness of the new approach. A systematic comparison between the existing work and the proposed work also has been given. Show more

Keywords: GIVPFEWA operator, GIVPFEOWA operator, GIVPFEHA operator, Group decision-making

DOI: 10.3233/JIFS-182951

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-22, 2019

Authors: Nguyen, Linh Anh | Nguyen, Ngoc-Thanh

Article Type: Research Article

Abstract:  We study the problem of minimizing interpretations in fuzzy description logics (DLs) under the Gödel semantics by using fuzzy bisimulations. The considered logics are fuzzy extensions of the DL 𝒜ℒ𝒞reg (a variant of propositional dynamic logic) with additional features among inverse roles, nominals and the universal role. Given a fuzzy interpretation ℐ and for E being the greatest fuzzy auto-bisimulation of ℐ w.r.t. the considered DL, we define the quotient ℐ/E of ℐ w.r.t. E and prove that it is minimum w.r.t. certain criteria. Namely, ℐ/E is a minimum fuzzy interpretation that validates the same set …of fuzzy terminological axioms in the considered DL as ℐ. Furthermore, if the considered DL allows the universal role, then ℐ/E is a minimum fuzzy interpretation bisimilar to ℐ, as well as a minimum fuzzy interpretation that validates the same set of fuzzy concept assertions in the considered DL as ℐ. Show more

Keywords: fuzzy description logic, fuzzy bisimulation, bisimilarity, Gödel semantics, minimization

DOI: 10.3233/JIFS-179371

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Ramadan, Ahmed | Elkordy, Enas | Abdel-Hameed, Usama | Ahmed, Reham

Article Type: Research Article

Abstract: This paper is dedicated to introduce the concept of a new space named "L -fuzzy nearness" and to arise a great deal of relationships among it and most of known spaces, like: L -fuzzy topological spaces (interior, closure, co-topology) and L -fuzzy pre-proximities in complete residuated lattices. We have demonstrated concrete functors between the category of Alexandrov L -fuzzy nearness, Alexandrov L -fuzzy topological structures and Alexandrov L -fuzzy pre-proximities and established the Galois correspondence between these categories.

Keywords: Complete residuated lattice, L-fuzzy nearness, L-fuzzy pre-proximity, L-fuzzy topological spaces, Galois correspondence.

DOI: 10.3233/JIFS-182938

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Siemiński, Andrzej | Kopel, Marek

Article Type: Research Article

Abstract: The paper verifies the usefulness of a parallel and adaptive Ant Colony Communities (ACC) for solving the dynamic Travelling Salesman Problem (DTSP). ACC consists of a set of client colonies with a server to coordinate their work. Each one of the client colonies implements a standard ACO algorithm. The paper contains a detailed analysis of the operation of ACO for static TSP in order to identify its most dominant parameters. Graph Generator is used to modify the distances in TSP. In order to catch up with the constant changes the ACC should work in parallel and to adopt to the …current distances. This is accomplished by modifying the number of iterations and changing the size of its internal prospective solutions buffer. Two implementations of ACC are presented: an asynchronous that works on computers connected through a LAN and a synchronous that uses a Hadoop environment. Numerous experiments clearly indicate, that the adaptive, parallel ACC outperforms both standard version of ACO as well as its versions adopted for DTSP. This is especially true for highly dynamic Graph Generators. Show more

Keywords: Dynamic TSP, Ant Colony Community, PACO, immigrant based colonies, ACO parallel implementation

DOI: 10.3233/JIFS-179366

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Tabakov, Martin | Quesada, Joel

Article Type: Research Article

Abstract:  In this research, we succeeded in introducing a new reasoning procedure which applies interval type-2 fuzzy sets into a rule induction process. Our proposal allows information granulation which resulted in achieving good experimental results. We introduced decision tables with elements assumed as interval type-2 fuzzy sets which greatly generalize information. Next, by applying corresponding rule induction procedure, we introduced the possibility to generate directly from a benchmark data fuzzy rulebases for type-2 fuzzy inference models. We strongly believe that our reasoning approach will be a proper solution for different research issues such as classification or ranking procedures as well as …determining knowledge for fuzzy inference models. The method proposed was tested in a classification problem verified by using medical benchmark data. Show more

Keywords: Fuzzy sets, fuzzy reasoning, interval type-2 fuzzy sets, data classification, data discovery, pawlak’s information system, information granulation, rule induction, fuzzy rules

DOI: 10.3233/JIFS-179367

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019