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