Journal of Intelligent & Fuzzy Systems - Volume 40, issue 6

Authors: Ghosh, Arijit | Dey, Munmun | Mondal, Sankar Prasad | Shaikh, Azharuddin | Sarkar, Anirban | Chatterjee, Banashree

Article Type: Research Article

Abstract: E-Rickshaw is an E-vehicle that has three wheels, a rechargeable battery driven electric motor as engine. E-rickshaw has become very popular due to low operating cost, low maintenance cost, eco-friendliness and ease of driving. It is perfect for small distance transport. As a last mile connector, it has transformed the public transport system in India. The low cost electric vehicle carries enough people to make a decent income and hence has become a source of livelihood for many. For considering the issues in this paper, detailed attributes of E-rickshaw are studied and Analytical Hierarchy Process (AHP) has been applied to …calculate criteria weights for the sorted attributes. Subsequently, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a Multi Criteria Decision Making (MCDM) technique has been applied for the selection of best E-Rickshaw. In this paper, sensitivity analysis and comparative analysis have been conducted for further insight. Show more

Keywords: AHP method, E-Rickshaws selection, sensitivity analysis, TOPSIS method

DOI: 10.3233/JIFS-202406

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11217-11230, 2021

Authors: Mi, Xiangjun | Tian, Ye | Kang, Bingyi

Article Type: Research Article

Abstract: Describing and processing complex as well as ambiguous and uncertain information has always been an inescapable and challenging topic in multi-attribute decision analysis (MADA) problems. As an extension of Dempster-Shafer (D-S) evidence theory, D numbers breaks through the constraints of the constraint framework and is a new way of expressing uncertainty. The soft likelihood function based on POWA operator is one of the most useful tools recently developed for dealing with uncertain information, since it provides a more excellent performance for the aggregation of multiple compatible evidence. Recently, a new MADA model based on D numbers has been proposed, called …DMADA. In this paper, inspired by the above mentioned theories, based on soft likelihood functions, POWA aggregation and D numbers we design a novel model to improve the performance of representing and processing uncertain information in MADA problems as an improvement of the DMADA approach. In contrast, our advantages include mainly the following. Firstly, the proposed method considers the reliability characteristics of each initial D number information. Secondly, the proposed method empowers decision makers with the possibility to express their perceptions through attitudinal features. In addition, an interesting finding is that the preference parameter in the proposed method can clearly distinguish the variability between candidates by adjusting the space values between adjacent alternatives, making the decision results clearer. Finally, the effectiveness and superiority of this model are proved through analysis and testing. Show more

Keywords: Multi-attribute decision analysis (MADA), D numbers, ordered weighted averaging (OWA), power OWA (POWA), soft likelihood function (SLF), reliability

DOI: 10.3233/JIFS-202413

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11231-11255, 2021

Authors: Pei, Huili | Li, Hongliang | Liu, Yankui

Article Type: Research Article

Abstract: In practical decision-making problems, decision makers are often affected by uncertain parameters because the exact distributions of uncertain parameters are usually difficult to determine. In order to deal with this issue, the major contribution in this paper is to propose a new type of type-2 fuzzy variable called level interval type-2 fuzzy variable from the perspective of level-sets, which is a useful tool in modeling distribution uncertainty. With our level interval type-2 fuzzy variable, we give a method for constructing a parametric level interval (PLI) type-2 fuzzy variable from a nominal possibility distribution by introducing the horizontal perturbation parameters. The …proposed horizontal perturbation around the nominal distribution is different from the vertical perturbation discussed in the literature. In order to facilitate the modeling in practical decision-making problems, for a level interval type-2 fuzzy variable, we define its selection variable whose distribution can be determined via its level-sets. The numerical characteristics like expected value and second order moments are important indices in practical optimization and decision-making problems. With this consideration, we establish the analytical expressions about the expected values and second order moments of the selection variables of PLI type-2 trapezoidal, normal and log-normal fuzzy variables. Furthermore, in order to derive the analytical expressions about the numerical characteristics of the selection variable for the sums of the common PLI type-2 fuzzy variables, we discuss the arithmetic about the sums of common PLI type-2 fuzzy variables. Finally, we apply the proposed optimization method to a pricing decision problem to demonstrate the efficiency of our new method. The computational results show that even a small perturbation of the nominal possibility distribution can affect the quality of solutions. Show more

Keywords: Level interval type-2 fuzzy variable, Selection variable, Second order moments, Pricing decision

DOI: 10.3233/JIFS-202421

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11257-11272, 2021

Authors: Wang, Huiru | Zhou, Zhijian

Article Type: Research Article

Abstract: Multi-view learning utilizes information from multiple representations to advance the performance of categorization. Most of the multi-view learning algorithms based on support vector machines seek the separating hyperplanes in different feature spaces, which may be unreasonable in practical application. Besides, most of them are designed to balanced data, which may lead to poor performance. In this work, a novel multi-view learning algorithm based on maximum margin of twin spheres support vector machine (MvMMTSSVM) is introduced. The proposed method follows both maximum margin principle and consensus principle. By following the maximum margin principle, it constructs two homocentric spheres and tries to …maximize the margin between the two spheres for each view separately. To realize the consensus principle, the consistency constraints of two views are introduced in the constraint conditions. Therefore, it not only deals with multi-view class-imbalanced data effectively, but also has fast calculation efficiency. To verify the validity and rationlity of our MvMMTSSVM, we do the experiments on 24 binary datasets. Furthermore, we use Friedman test to verify the effectiveness of MvMMTSSVM. Show more

Keywords: Multi-view learning, twin spheres, SVM, maximum margin, consensus principle

DOI: 10.3233/JIFS-202427

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11273-11286, 2021

Authors: Liu, Peide | Mahmood, Tahir | Ali, Zeeshan

Article Type: Research Article

Abstract: Complex q-rung orthopair fuzzy set (CQROFS) is a proficient technique to describe awkward and complicated information by the truth and falsity grades with a condition that the sum of the q-powers of the real part and imaginary part is in unit interval. Further, Schweizer–Sklar (SS) operations are more flexible to aggregate the information, and the Muirhead mean (MM) operator can examine the interrelationships among the attributes, and it is more proficient and more generalized than many aggregation operators to cope with awkward and inconsistence information in realistic decision issues. The objectives of this manuscript are to explore the SS operators …based on CQROFS and to study their score function, accuracy function, and their relationships. Further, based on these operators, some MM operators based on PFS, called complex q-rung orthopair fuzzy MM (CQROFMM) operator, complex q-rung orthopair fuzzy weighted MM (CQROFWMM) operator, and their special cases are presented. Additionally, the multi-criteria decision making (MCDM) approach is developed by using the explored operators based on CQROFS. Finally, the advantages and comparative analysis are also discussed. Show more

Keywords: Complex q-rung orthopair fuzzy sets, Schweizer-Sklar Muirhead means operators, multi-criteria decision making

DOI: 10.3233/JIFS-202440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11287-11309, 2021

Authors: Xuan, Cho Do | Duong, Duc | Dau, Hoang Xuan

Article Type: Research Article

Abstract: Advanced Persistent Threat (APT) is a dangerous network attack method that is widely used by attackers nowadays. During the APT attack process, attackers often use advanced techniques and tools, thus, causing many difficulties for information security systems. In fact, to detect the APT attacks, intrusion detection systems cannot rely on one technique or method but often combine multiple techniques and methods. In addition, the approach for APT attack detection using behavior analysis and evaluation techniques is facing many difficulties due to the lack of characteristic data of attack campaigns. For the above reasons, in this paper, we propose a method …for APT attack detection based on a multi-layer analysis. The multi-layer analysis technique in our proposal computes and analyzes various events in Network Traffic to detect and synthesize abnormal signs and behaviors in order to make conclusions about the existence of APT in the system. Specifically, in our proposal, we will use serial 3 main layers for the APT attack detection process including i) Detecting APT attacks based on analyzing abnormal connection; ii) Detecting APT attacks based on analyzing and evaluating Suricata log; iii) Detecting APT attacks based on analyzing behavior profiles that are compiled from layers (i) and (ii). To achieve these goals, the multi-layer analysis technique for APT attack detection will perform 2 main tasks: i) Analyzing and evaluating components of Network Traffic based on abnormal signs and behaviors. ii) building and classifying behavior profile based on each component of network traffic. In the experimental section, we will compare and evaluate the effectiveness of the APT attack detection process of each layer in the multi-layer analysis model using machine learning. Experimental results have shown that the APT attack detection method based on analyzing behavior profile has yielded better results than individual detection methods on all metrics. The research results shown in the paper not only demonstrate the effectiveness of the multilayer analysis model for APT attack detection but also provide a novel approach for detecting several other cyber-attack techniques. Show more

Keywords: Advanced persistent threat, APT attack detection, network traffic, multi-layer detection, abnormal behavior, machine learning

DOI: 10.3233/JIFS-202465

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11311-11329, 2021

Authors: Revathi, T. | Rajalaxmi, T.M. | Sundara Rajan, R. | Freire, Wilhelm Passarella

Article Type: Research Article

Abstract: Salient object detection plays a vital role in image processing applications like image retrieval, security and surveillance in authentic-time. In recent times, advances in deep neural network gained more attention in the automatic learning system for various computer vision applications. In order to decrement the detection error for efficacious object detection, we proposed a detection classifier to detect the features of the object utilizing a deep neural network called convolutional neural network (CNN) and discrete quaternion Fourier transform (DQFT). Prior to CNN, the image is pre-processed by DQFT in order to handle all the three colors holistically to evade loss …of image information, which in-turn increase the effective use of object detection. The features of the image are learned by training model of CNN, where the CNN process is done in the Fourier domain to quicken the method in productive computational time, and the image is converted to spatial domain before processing the fully connected layer. The proposed model is implemented in the HDA and INRIA benchmark datasets. The outcome shows that convolution in the quaternion Fourier domain expedite the process of evaluation with amended detection rate. The comparative study is done with CNN, discrete Fourier transforms CNN, RNN and masked RNN. Show more

Keywords: Convolutional neural networks, quaternion complex variable, object detection, image enhancement, discrete quaternion Fourier transform

DOI: 10.3233/JIFS-202502

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11331-11340, 2021

Authors: Beseiso, Majdi | Kumar, Gulshan

Article Type: Research Article

Abstract: This paper presents a fuzzy computational approach for selecting project portfolio by combining fuzzy logic, Quality Function Deployment (QFD) and Genetic algorithm (GA) approaches with the consideration of prioritized selection criteria as per objectives of the organization to make decisions effectively with incomplete and ambiguous information to help in portfolio selection. This approach addresses the issues of the uncertainty of experts in selecting projects, prioritizing criteria before initiating project selection process and evaluating the number of interdependent projects for their maximal values. It completes the task in three stages. Firstly, it involves interaction with experts to extract fuzzy input about …the benefits of organization and selection criteria for selecting a project portfolio. The second stage requires the application of fuzzy QFD to prioritize criteria before deciding the project portfolio. In this stage, the paper contributes a method for using fuzzy values in a distinct way for obtaining priorities of selection criteria. The final stage evaluates the candidate projects concurrently based on top priority selection criteria by considering interrelation among projects by proposing a distinct fitness function of GA. The validity of the proposed approach is demonstrated by an example that considers three experts, three objectives of the organization and four selection criteria. Show more

Keywords: Fuzzy quality function development (FQFD), genetic algorithm, project portfolio management, project portfolio selection, quality function development (QFD)

DOI: 10.3233/JIFS-202506

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11341-11354, 2021

Authors: Khan, Vakeel A. | Tuba, Umme | Ashadul Rahaman, SK. | Ahmad, Ayaz

Article Type: Research Article

Abstract: In 1990, Diamond [16 ] primarily established the base of fuzzy star–shaped sets, an extension of fuzzy sets and numerous of its properties. In this paper, we aim to generalize the convergence induced by an ideal defined on natural numbers ℕ , introduce new sequence spaces of fuzzy star–shaped numbers in ℝ n and examine various algebraic and topological properties of the new corresponding spaces as well. In support of our results, we provide several examples of these new resulting sequences.

Keywords: Fuzzy star–shaped numbers, Lp–metric, I–convergence, solidity and convergence free

DOI: 10.3233/JIFS-202534

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11355-11362, 2021

Authors: Aydoğmuş, Hacer Yumurtacı | Kamber, Eren | Kahraman, Cengiz

Article Type: Research Article

Abstract: The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human’s judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture fuzzy uncertainty based on Euclidean and …Taxicab distances and negative ideal solution. ERP system selection problem is handled as the application area of the developed method, picture fuzzy CODAS. Results indicate that the new proposed method finds meaningful rankings through picture fuzzy sets. Comparative analyzes show that the presented method gives successful and robust results for the solutions of MCDM problems under fuzziness. Show more

Keywords: Fuzzy, picture fuzzy sets, CODAS method, ERP selection

DOI: 10.3233/JIFS-202564

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11363-11373, 2021

Authors: Chou, ShuoYan | Duong, Truong Thi Thuy | Thao, Nguyen Xuan

Article Type: Research Article

Abstract: Energy plays a central part in economic development, yet alongside fossil fuels bring vast environmental impact. In recent years, renewable energy has gradually become a viable source for clean energy to alleviate and decouple with a negative connotation. Different types of renewable energy are not without trade-offs beyond costs and performance. Multiple-criteria decision-making (MCDM) has become one of the most prominent tools in making decisions with multiple conflicting criteria existing in many complex real-world problems. Information obtained for decision making may be ambiguous or uncertain. Neutrosophic is an extension of fuzzy set types with three membership functions: truth membership function, …falsity membership function and indeterminacy membership function. It is a useful tool when dealing with uncertainty issues. Entropy measures the uncertainty of information under neutrosophic circumstances which can be used to identify the weights of criteria in MCDM model. Meanwhile, the dissimilarity measure is useful in dealing with the ranking of alternatives in term of distance. This article proposes to build a new entropy and dissimilarity measure as well as to construct a novel MCDM model based on them to improve the inclusiveness of the perspectives for decision making. In this paper, we also give out a case study of using this model through the process of a renewable energy selection scenario in Taiwan performed and assessed. Show more

Keywords: Dissimilarity measure, renewable energy, interval neutrosophic set

DOI: 10.3233/JIFS-202571

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11375-11392, 2021

Authors: Zhang, Chengling | Li, Jinjin | Lin, Yidong

Article Type: Research Article

Abstract: Three-way concept analysis is a mathematical model of the combination of formal concept analysis and three-way decision, and knowledge discovery plays a significant impact on formal fuzzy contexts since such datasets are frequently encountered in real life. In this paper, a novel type of one-sided fuzzy three-way concept lattices is presented in a given formal fuzzy context with its complement, in which a ternary classification is available. In such case, we comprehensively explore the connections between the proposed models and classical fuzzy concept lattices among elements, sets, and orders. Furthermore, approaches to granular matrix-based reductions are investigated, by which granular …consistent sets, and granular reducts via discernibility Boolean matrices are tectonically put forward. At last, the demonstrated results are performed by several experiments which enrich the research of three-way concept analysis. Show more

Keywords: Formal fuzzy contexts, granular reduction, one-sided fuzzy concept lattices, three-way decision

DOI: 10.3233/JIFS-202573

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11393-11410, 2021

Authors: Malini, A. | Priyadharshini, P. | Sabeena, S.

Article Type: Research Article

Abstract: To develop a surveillance and detection system for automating the process of road maintenance work which is being carried out by surveying and inspection of roads manually in the current situation. The need of the system lies in the fact that traditional methods are time-consuming, tiresome and require huge workforce. This paper proposes an automation system using Unmanned Aerial Vehicle which monitors and detects the pavement defects like cracks and potholes by processing real-time video footage of Indian highways. The collected data is processed and stored as images in a road defects database which serves as input for the system. …The behavior of Region Proposal Network (RPN) is made smooth by varying the number of region proposals utilized in the model. A regularization technique called dropout is used to achieve higher performance in the proposed Faster Region based Convolutional Neural Networks object detection model. The detections are made with 62.3% mean Average Precision @ Intersection over Union (IoU)> = 0.5 for the generation of 300 region proposals which is a good score for object detections. The comparisons between proposed and existing systems shows that the proposed Faster RCNN with modified VGG-16 performs well than the existing variants. Show more

Keywords: pothole, region proposal network, mean average precision, unmanned aerial vehicle, dropout

DOI: 10.3233/JIFS-202596

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11411-11422, 2021

Authors: Liu, Hui | He, Boxia | He, Yong | Tao, Xiaotian

Article Type: Research Article

Abstract: The existing seal ring surface defect detection methods for aerospace applications have the problems of low detection efficiency, strong specificity, large fine-grained classification errors, and unstable detection results. Considering these problems, a fine-grained seal ring surface defect detection algorithm for aerospace applications is proposed. Based on analysis of the stacking process of standard convolution, heat maps of original pixels in the receptive field participating in the convolution operation are quantified and generated. According to the generated heat map, the feature extraction optimization method of convolution combinations with different dilation rates is proposed, and an efficient convolution feature extraction network containing …three kinds of dilated convolutions is designed. Combined with the O-ring surface defect features, a multiscale defect detection network is designed. Before the head of multiscale classification and position regression, feature fusion tree modules are added to ensure the reuse and compression of the responsive features of different receptive fields on the same scale feature maps. Experimental results show that on the O-rings-3000 testing dataset, the mean condition accuracy of the proposed algorithm reaches 95.10% for 5 types of surface defects of aerospace O-rings. Compared with RefineDet, the mean condition accuracy of the proposed algorithm is only reduced by 1.79%, while the parameters and FLOPs are reduced by 35.29% and 64.90%, respectively. Moreover, the proposed algorithm has good adaptability to image blur and light changes caused by the cutting of imaging hardware, thus saving the cost. Show more

Keywords: Deep learning, feature extraction network, lightweight algorithm, multiscale classification, surface defect detection, O-rings

DOI: 10.3233/JIFS-202614

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11423-11440, 2021

Authors: Naderi, Katayoun | Ahari, Roya M. | Jouzdani, Javid | Amindoust, Atefeh

Article Type: Research Article

Abstract: Fierce competition in the global markets forced companies to improve the design and management of supply chains, because companies are always looking for more profit and higher customer satisfaction. The emergence of the green supply chain is one of the most important developments of the last decade. It provides an opportunity for companies to adjust their supply chains according to environmental goals and sustainability. The integrated production-inventory-routing is a new field that aims to optimize these three decision-making levels. It can be described as follow: a factory produces one or more products, and sells them to several customers (by direct …delivery or a specific customer chain). The current study aims to model a production-inventory-routing system using a system dynamics approach to design a green supply chain under uncertain conditions. For this purpose, first, the association between selected variables was determined. Then, the proposed model was validated. Finally, to identify variables with the highest influence, four scenarios were developed. The results indicated that minimum total transportation cost, the total warehouse capacity of the supply chain, and the maximum production rate are the most influential strategies to achieve ideal condition. Show more

Keywords: System dynamics, integrated production-inventory-routing problem, green supply chain, uncertainty

DOI: 10.3233/JIFS-202622

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11441-11454, 2021

Authors: Yao, Wei | Chen, Ye

Article Type: Research Article

Abstract: The arity of convex spaces is a numerical feature which shows the ability of finite subsets spanning to the whole space via the hull operators. This paper gives it a formal and strict definition by introducing the truncation of convex spaces. The relations that between the arity of quotient spaces and the original spaces, that between the arity of subspaces and superspaces, that between the arity of product spaces and factors spaces, and that between the arity of disjoint sums and term spaces, are systematically studied. A mistake of a formula in [M. Van De Vel, Theory of Convex Structures, …North-Holland, Amsterdam, 1993] is corrected. It is shown that a convex space is Alexandrov iff its arity is 1. The convex structures with arity ≤n are equivalent to structured sets with n -restricted hull operators. Show more

Keywords: convex space, arity, product space, disjoint sum, n-restricted hull operator

DOI: 10.3233/JIFS-202643

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11455-11462, 2021

Authors: Saravana Kumar, P. | Vasuki, S.

Article Type: Research Article

Abstract: In chromosome analysis, centromere is an essential component. By analyzing centromere, genetic disorder can be identified easily. In this paper, automatic classification and centromere detection in human chromosome image using Band Distance Feature is proposed. Initially the microscopic image of G-band chromosome is preprocessed in order to remove the blobs. Then, the image is segmented using labelling algorithm and the endpoints are calculated. Now, the overlapping chromosomes are removed when the number of end points is greater than two. The non-overlapped chromosomes are straightened using Reversible Projection algorithm. From the straightened chromosome band distance feature is calculated. The extracted features …are given to the ANN classifier to identify the class of chromosome and to calculate the centromere. From the experimental results, it is observed that the proposed method is superior to the traditional method. Show more

Keywords: Artificial neural networks, chromosome classification, labeling algorithm, straightening algorithm

DOI: 10.3233/JIFS-202682

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11463-11474, 2021

Authors: Hadi, Sarem H. | Madhi, Zainab S. | Park, Choonkil

Article Type: Research Article

Abstract: The purpose of this study is to introduce a new concept of the modular space, which is C Ω -modular space, and then some of the convex properties are discussed. We also study finding fixed-point in C Ω -modular space.

Keywords: CΩ-modular space, 𝒢-convergence, 𝒢-Cauchy sequence, fixed-point in CΩ-modular space

DOI: 10.3233/JIFS-202698

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11475-11478, 2021

Authors: Naeem, Muhammad | Khan, Muhammad Ali | Abdullah, Saleem | Qiyas, Muhammad | Khan, Saifullah

Article Type: Research Article

Abstract: Probabilistic hesitant fuzzy Set (PHFs) is the most powerful and comprehensive idea to support more complexity than developed fuzzy set (FS) frameworks. In this paper a novel and improved TOPSIS-based method for multi-criteria group decision making (MCGDM) is explained through the probabilistic hesitant fuzzy environment, in which the weights of both experts and criteria are completely unknown. Firstly, we discuss the concept of PHFs, score functions and the basic operating laws of PHFs. In fact, to compute the unknown weight information, the generalized distance measure for PHFs was defined based on the Probabilistic hesitant fuzzy entropy measure. Second, MCGDM will …be presented with the PHF information-based decision-making process. Show more

Keywords: Probabilistic hesitant fuzzy Set, extended TOPSIS method, application in decision making

DOI: 10.3233/JIFS-202700

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11479-11490, 2021

Authors: Jia, Xiang | Wang, Xinfan | Zhu, Yuanfang | Zhou, Lang | Zhou, Huan

Article Type: Research Article

Abstract: This study proposes a two-sided matching decision-making (TSMDM) approach by combining the regret theory under the intuitionistic fuzzy environment. At first, according to the Hamming distance of intuitionistic fuzzy sets and regret theory, superior and inferior flows are defined to describe the comparative preference of subjects. Hereafter, the satisfaction degrees are obtained by integrating the superior and inferior flows of the subjects. The comprehensive satisfaction degrees are calculated by aggregating the satisfaction degrees, based on which, a multi-objective TSMDM model is built. Furthermore, the multi-objective TSMDM model is converted to a single-objective model, the optimal solution of the latter is …derived. Finally, an illustrative example and several analyses are provided to verify the feasibility and the effectiveness of the proposed approach. Show more

Keywords: Multi-criteria decision-making, intuitionistic fuzzy sets, regret theory, two-sided matching, optimal model

DOI: 10.3233/JIFS-202720

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11491-11508, 2021

Authors: Fang, HaiFeng | Cao, Jin | Cai, LiHua | Zhou, Ta | Wang, MingQiang

Article Type: Research Article

Abstract: Both classification rate and accuracy are crucial for the recyclable PET bottles, and the existing combination methods of SVM all simply use SVM as the unit classifier, ignoring the improvement of SVM’s classification performance in the training process of deep learning. A linear multi hierarchical deep structure based on Support Vector Machine (SVM) is proposed to cover this problem. A novel definition of the input matrix in each layer enhances the optimization of Lagrange multipliers in Sequential Minimal Optimization (SMO) algorithm, thus the datapoint in maximum interval of SVM hyperplane could be recognized, improving the classification performance of SVM classifier …in this layer. The loss function defined in this paper could control the depth of Linear Multi Hierarchical SVM (LMHSVM), the generalization parameters are added in the loss function and the input matrix to enhance the generalization performance of LMHSVM. The process of creating Bottle dataset by Histogram of Oriented Gradient (HOG) and Principal Component Analysis (PCA) is introduced meanwhile, reducing the data size of bottles. Experiments are conducted on LMHSVM and multiple typical classification algorithms with Bottle dataset and UCI datasets, the results indicated that LMHSVM has excellent classification performances than FNN classifier, LIBSVM (Gaussian) and GFS-AdaBoost-C in KEEL. Show more

Keywords: Recycling plastic bottles, deep learning structure, SVM, Linear multi hierarchical, extract dataset

DOI: 10.3233/JIFS-202729

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11509-11522, 2021

Authors: Fan, Jianping | Yan, Feng | Wu, Meiqin

Article Type: Research Article

Abstract: In this article, the gained and lost dominance score (GLDS) method is extended into the 2-tuple linguistic neutrosophic environment, which also combined the power aggregation operator with the evaluation information to deal with the multi-attribute group decision-making problem. Since the power aggregation operator can eliminate the effects of extreme evaluating data from some experts with prejudice, this paper further proposes the 2-tuple linguistic neutrosophic numbers power-weighted average operator and 2-tuple linguistic neutrosophic numbers power-weighted geometric operator to aggregate the decision makers’ evaluation. Moreover, a model based on the score function and distance measure of 2-tuple linguistic neutrosophic numbers (2TLNNs) is …developed to get the criteria weights. Combing the GLDS method with 2-tuple linguistic neutrosophic numbers and developing a 2TLNN-GLDS method for multiple attribute group decision making, it can express complex fuzzy information more conveniently in a qualitative environment and also consider the dominance relations between alternatives which can get more effective results in real decision-making problems. Finally, an applicable example of selecting the optimal low-carbon logistics park site is given. The comparing results show that the proposed method outperforms the other existing methods, as it can get more reasonable results than others and it is more convenient and effective to express uncertain information in solving realistic decision-making problems. Show more

Keywords: Multiple attribute group decision making, 2-tuple linguistic neutrosophic numbers, power average operator, power geometric operator, the gained and lost dominance score method

DOI: 10.3233/JIFS-202748

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11523-11538, 2021

Authors: Zhang, Yongjie | Cao, Kang | Liang, Ke | Zeng, Yongqi

Article Type: Research Article

Abstract: Commonality, a typical commercial feature of serialized civil aircraft study and development, refers to a series of methods of reusing and sharing assets, which were developed based on broad similarity. The common design of serialized civil aircraft is capable of maximally saving R&D, production, operation, and disposal. To maximize the total benefits of manufacturers and operators, the common design of serialized civil aircrafts primarily exploits the commercial experience of serialized products in other fields (e.g., automobiles and mobile phones), whereas a scientific index system and quantitative evaluation model has not been formed. Accordingly, this study proposes a new civil aircraft …commonality index evaluation model in accordance with fuzzy set theory and methods. The model follows two branches, i.e., attribute commonality and structural commonality, to develop a multi-level civil aircraft commonality index system. The proposed model can split the commonality into six commonality sub-intervals and build the corresponding standard fuzzy set with the characteristic attribute parameters of the civil aircraft as the elements. Next, based on considerable civil aircraft sample data, a fuzzy test is designed to yield the membership function of the fuzzy set. Thus, a model of evaluating civil aircraft commonality is constructed, taking the characteristic parameters of the civil aircraft to be evaluated as input, and selecting the degree of commonality of each level as output. Lastly, this study employs the evaluation model to evaluate the commonality of Boeing 757-200 with other civil aircrafts. Furthermore, the evaluated results well explain the actual situation, which verifies the effectiveness and practicability of the proposed model. Show more

Keywords: Cost benefit analysis, serialized civil aircraft, commonality index, fuzzy set, membership function

DOI: 10.3233/JIFS-202749

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11539-11558, 2021

Authors: Li, Chunhua | Xu, Baogen | Huang, Huawei

Article Type: Research Article

Abstract: In this paper, the notion of a fuzzy *–ideal of a semigroup is introduced by exploiting generalized Green’s relations L * and R * , and some characterizations of fuzzy *–ideals on an arbitrary semigroup are obtained. Our main purpose is to establish the relationship between fuzzy *–ideals and abundance for an arbitrary semigroup. As an application of our results, we also give some new necessary and sufficient conditions for an arbitrary semigroup to be regular and inverse, respectively.

Keywords: fuzzy*–ideals, abundant semigroups, abundance, 20M20

DOI: 10.3233/JIFS-202759

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11559-11566, 2021

Authors: Wu, Yaoqiang

Article Type: Research Article

Abstract: In this paper, we introduce the concept of weak partial-quasi k-metrics, which generalizes both k-metric and weak metric. Also, we present some examples to support our results. Furthermore, we obtain some fixed point theorems in weak partial-quasi k-metric spaces.

Keywords: weak metric, k-metric, partial-quasi k-metric, weak partial-quasi k-metric, fixed point theorem

DOI: 10.3233/JIFS-202768

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11567-11575, 2021

Authors: Luo, D. | Zhang, G.Z.

Article Type: Research Article

Abstract: The purpose of this paper is to solve the prediction problem of nonlinear sequences with multiperiodic features, and a multiperiod grey prediction model based on grey theory and Fourier series is established. For nonlinear sequences with both trend and periodic features, the empirical mode decomposition method is used to decompose the sequences into several periodic terms and a trend term; then, a grey model is used to fit the trend term, and the Fourier series method is used to fit the periodic terms. Finally, the optimization parameters of the model are solved with the objective of obtaining a minimum mean …square error. The novel model is applied to research on the loss rate of agricultural droughts in Henan Province. The average absolute error and root mean square error of the empirical analysis are 0.3960 and 0.5086, respectively. The predicted results show that the novel model can effectively fit the loss rate sequence. Compared with other models, the novel model has higher prediction accuracy and is suitable for the prediction of multiperiod sequences. Show more

Keywords: Nonlinear sequences, multiperiod, grey model, empirical mode decomposition, Fourier series

DOI: 10.3233/JIFS-202775

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11577-11586, 2021

Authors: Yang, Xu | Guo, Yu | Liu, Qiang | Zhang, Deming

Article Type: Research Article

Abstract: Effective enterprise quality immune response can grasp the “pathogenesis”, “clinical manifestations” and “treatment” of enterprise quality dissident factors, which is the goal pursued continuously by enterprise quality management. Drawing on the theory of enterprise immunity, construct the evaluation index system of enterprise quality immune response effect, and use the evaluation model of interval binary semantic grey target decision based on two-dimensional association sampling (EMIBSGTD-TAS) to evaluate the quality immune response effect of the selected target company. The boundary and internal distribution situation weaken the influence of the extreme value of the index on the decision result, and introduce the interval …binary semantic set value statistical method to determine the index weight, reduce the information loss and fuzzy error. It can be seen from the evaluation results that the model has practicability and feasibility, and provides a new idea for the evaluation of the effect of enterprise quality immune response. Show more

Keywords: Quality Immune Response, Two-dimensional Association Sampling (TAS), Interval Binary Semantics (IBS), Gray Target Decision (GTD)

DOI: 10.3233/JIFS-202794

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11587-11606, 2021

Authors: Ya-Na, Wang | Guo-Hua, Zhou

Article Type: Research Article

Abstract: The aim of this paper is to investigate a profit-maximization firm how to determine the composition and prices of multiple bundles. Bundles are sets of components that must meet some technical constraints; furthermore, customers differ in their quality valuations and choose the bundle that maximizes their utility. A mixed integer non-linear program is proposed to solve this problem. First, a two-step approach is employed to obtain the firm’s optimal decision. The result indicates that when the firm faces deterministic demand, the optimal set of bundles it offers is independent of the distribution of customer valuations and does not contain any …dominated bundle. In addition, dominated components cannot be used to construct the optimal bundles. Second, the impact of demand uncertainty on the firm’s performance is explored. The results suggest that disregarding the demand risk may result in broader assortment and suboptimal prices. Finally, numerical experiments and sensitive analysis are conducted to provide managerial insights for the pricing and composition of multiple bundles. Show more

Keywords: Vertical differentiation, uncertain demand, pricing, composition of bundle, consumer choice model

DOI: 10.3233/JIFS-202799

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11607-11623, 2021

Authors: Norouzi, Ashraf | hajiagha, Hossein Razavi

Article Type: Research Article

Abstract: Multi criteria decision-making problems are usually encounter implicit, vague and uncertain data. Interval type-2 fuzzy sets (IT2FS) are widely used to develop various MCDM techniques especially for cases with uncertain linguistic approximation. However, there are few researches that extend IT2FS-based MCDM techniques into qualitative and group decision-making environment. The present study aims to adopt a combination of hesitant and interval type-2 fuzzy sets to develop an extension of Best-Worst method (BWM). The proposed approach provides a flexible and convenient way to depict the experts’ hesitant opinions especially in group decision-making context through a straightforward procedure. The proposed approach is called …IT2HF-BWM. Some numerical case studies from literature have been used to provide illustrations about the feasibility and effectiveness of our proposed approach. Besides, a comparative analysis with an interval type-2 fuzzy AHP is carried out to evaluate the results of our proposed approach. In each case, the consistency ratio was calculated to determine the reliability of results. The findings imply that the proposed approach not only provides acceptable results but also outperforms the traditional BWM and its type-1 fuzzy extension. Show more

Keywords: Best-worst method (BWM), hesitant fuzzy linguistic term set, hesitant interval type-2 Fuzzy BWM, interval type-2 fuzzy set, multi-attribute decision-making, qualitative decision-making

DOI: 10.3233/JIFS-202801

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11625-11652, 2021

Authors: Nguyen, Trang T.D. | Nguyen, Loan T.T. | Nguyen, Anh | Yun, Unil | Vo, Bay

Article Type: Research Article

Abstract: Spatial clustering is one of the main techniques for spatial data mining and spatial data analysis. However, existing spatial clustering methods primarily focus on points distributed in planar space with the Euclidean distance measurement. Recently, NS-DBSCAN has been developed to perform clustering of spatial point events in Network Space based on a well-known clustering algorithm, named Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The NS-DBSCAN algorithm has efficiently solved the problem of clustering network constrained spatial points. When compared to the NC_DT (Network-Constraint Delaunay Triangulation) clustering algorithm, the NS-DBSCAN algorithm efficiently solves the problem of clustering network constrained spatial …points by visualizing the intrinsic clustering structure of spatial data by constructing density ordering charts. However, the main drawback of this algorithm is when the data are processed, objects that are not specifically categorized into types of clusters cannot be removed, which is undeniably a waste of time, particularly when the dataset is large. In an attempt to have this algorithm work with great efficiency, we thus recommend removing edges that are longer than the threshold and eliminating low-density points from the density ordering table when forming clusters and also take other effective techniques into consideration. In this paper, we develop a theorem to determine the maximum length of an edge in a road segment. Based on this theorem, an algorithm is proposed to greatly improve the performance of the density-based clustering algorithm in network space (NS-DBSCAN). Experiments using our proposed algorithm carried out in collaboration with Ho Chi Minh City, Vietnam yield the same results but shows an advantage of it over NS-DBSCAN in execution time. Show more

Keywords: Spatial data mining, spatial data clustering, NS-DBSCAN, network spatial analysis

DOI: 10.3233/JIFS-202806

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11653-11670, 2021

Authors: Özgül, Ercan | Dinçer, Hasan | Yüksel, Serhat

Article Type: Research Article

Abstract: Healthy life is recognized as one of the most fundamental human rights. However, even today, millions of people around the world are forced to choose between their basic needs and fundamental rights. Half of the world’s population does not have access to the healthcare they need. Universal Health Coverage (UHC) aims to ensure that all individuals receive the quality health services they need without incurring a financial burden, and to protect them from risk factors that threaten their health. The aim of this study is to identify the significant factors to improve UHC in the countries. For this purpose, house …of quality (HoQ) approach is used in the analysis process so that both customer expectations and technical requirements are considered. Within this framework, a novel hybrid model has been proposed which has three different stages. Firstly, 3 groups of diseases and 4 clinical services for each group are determined regarding the customer needs. Secondly, these factors are weighted by using interval-valued intuitionistic hesitant 2-tuple fuzzy decision making and trial evaluation laboratory (DEMATEL). In the final stage, 9 different technical requirements are ranked by using interval-valued intuitionistic hesitant 2-tuple fuzzy technique for order preference by similarity to ideal solution (TOPSIS). Additionally, another evaluation has also been conducted by considering Spherical fuzzy sets. Similarly, a comparative analysis has also been performed with VIKOR while ranking the alternatives. It is concluded that analysis results of both evaluations are quite similar. This situation gives an information about the coherency and consistency of the analysis results. The findings indicate that treatment services in noncommunicable diseases play the most significant role in this respect. Moreover, according to the ranking results, it is concluded that strategic policies should be related to improving the social security and special physician capacity as well as decreasing the out-of-pocket payment. Show more

Keywords: House of quality, UHC, hesitant linguistic terms, DEMATEL, TOPSIS

DOI: 10.3233/JIFS-202818

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11671-11689, 2021

Authors: Liu, Rui-Lin | Yang, Hai-Long | Zhang, Li-Juan

Article Type: Research Article

Abstract: This paper studies information structures in a fuzzy β -covering information system. We introduce the concepts of a fuzzy β -covering information system and homomorphism between them, and investigate related properties. The concept of information structure of a fuzzy β -covering information system is given. We discuss the relationships between information structures from the view of dependence and separation. Then granularity measures for a fuzzy β -covering information system are studied. Finally, we discuss invariance of fuzzy β -covering information systems under homomorphism and illustrate its application on data compression.

Keywords: Fuzzy β-covering, fuzzy β-covering information system, information structure, homomorphism, invariance property

DOI: 10.3233/JIFS-202824

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11691-11716, 2021

Authors: Wang, Fubin | Liu, Peide | Wang, Peng

Article Type: Research Article

Abstract: A scientific evaluation model can be effectively used for the evaluation of regional talent development level. This paper proposes a set of scientific index systems for evaluating rural science and technology talents, which can be used for understanding the development status and level of rural science and technology talents in various regions; putting forward the corresponding talent cultivation and introduction policies, and; promoting the development of rural economic construction. Moreover, in order to avoid the shortcoming of over-subjective indicator weight in analytic hierarchy process (AHP), this paper uses the entropy weight method to determine indicator weight. Furthermore, giving the fact …that the evaluation experts may have individual personal preferences, this paper proposes an extended TODIM method based on hybrid index values, for achieving more scientific and effective evaluation results of rural science and technology talents. Finally, the proposed methods are evaluated on an actual case, where relevant analysis and suggestions are given. Show more

Keywords: Rural scientific and technological talents, TODIM method, entropy weight method, hybrid indicator, multi-attribute decision-making

DOI: 10.3233/JIFS-202847

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11717-11730, 2021

Authors: Ju, Hongmei | Zhang, Yafang | Zhao, Ye

Article Type: Research Article

Abstract: Classification problem is an important research direction in machine learning. υ -nonparallel support vector machine (υ -NPSVM) is an important classifier used to solve classification problems. It is widely used because of its structural risk minimization principle, kernel trick, and sparsity. However, when solving classification problems, υ -NPSVM will encounter the problem of sample noises and heteroscedastic noise structure, which will affect its performance. In this paper, two improvements are made on the υ -NPSVM model, and a υ-nonparallel parametric margin fuzzy support vector machine (par-υ -FNPSVM) is established. On the one hand, for the noises that may exist in …the data set, the neighbor information is used to add fuzzy membership to the samples, so that the contribution of each sample to the classification is treated differently. On the other hand, in order to reduce the effect of heteroscedastic structure, an insensitive loss function is introduced. The advantages of the new model are verified through UCI machine learning standard data set experiments. Finally, Friedman test and Bonferroni-Dunn test are used to verify the statistical significance of it. Show more

Keywords: Classification problem, sample noises, heteroscedastic noise structure, ν-nonparallel support vector machine, parameter margin, nearest neighbor fuzzy membership

DOI: 10.3233/JIFS-202869

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11731-11747, 2021

Authors: Pavan Kumar, C.S. | Dhinesh Babu, L.D.

Article Type: Research Article

Abstract: Sentiment analysis is widely used to retrieve the hidden sentiments in medical discussions over Online Social Networking platforms such as Twitter, Facebook, Instagram. People often tend to convey their feelings concerning their medical problems over social media platforms. Practitioners and health care workers have started to observe these discussions to assess the impact of health-related issues among the people. This helps in providing better care to improve the quality of life. Dementia is a serious disease in western countries like the United States of America and the United Kingdom, and the respective governments are providing facilities to the affected people. …There is much chatter over social media platforms concerning the patients’ care, healthy measures to be followed to avoid disease, check early indications. These chatters have to be carefully monitored to help the officials take necessary precautions for the betterment of the affected. A novel Feature engineering architecture that involves feature-split for sentiment analysis of medical chatter over online social networks with the pipeline is proposed that can be used on any Machine Learning model. The proposed model used the fuzzy membership function in refining the outputs. The machine learning model has obtained sentiment score is subjected to fuzzification and defuzzification by using the trapezoid membership function and center of sums method, respectively. Three datasets are considered for comparison of the proposed and the regular model. The proposed approach delivered better results than the normal approach and is proved to be an effective approach for sentiment analysis of medical discussions over online social networks. Show more

Keywords: Dementia, sentiment analysis, machine learning, FDA, feature-split, feature engineering, trapezoid membership function

DOI: 10.3233/JIFS-202874

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11749-11761, 2021

Authors: Zargari, Hamed | Zahedi, Morteza | Rahimi, Marziea

Article Type: Research Article

Abstract: Words are one of the most essential elements of expressing sentiments in context although they are not the only ones. Also, syntactic relationships between words, morphology, punctuation, and linguistic phenomena are influential. Merely considering the concept of words as isolated phenomena causes a lot of mistakes in sentiment analysis systems. So far, a large amount of research has been conducted on generating sentiment dictionaries containing only sentiment words. A number of these dictionaries have addressed the role of combinations of sentiment words, negators, and intensifiers, while almost none of them considered the heterogeneous effect of the occurrence of multiple linguistic …phenomena in sentiment compounds. Regarding the weaknesses of the existing sentiment dictionaries, in addressing the heterogeneous effect of the occurrence of multiple intensifiers, this research presents a sentiment dictionary based on the analysis of sentiment compounds including sentiment words, negators, and intensifiers by considering the multiple intensifiers relative to the sentiment word and assigning a location-based coefficient to the intensifier, which increases the covered sentiment phrase in the dictionary, and enhanced efficiency of proposed dictionary-based sentiment analysis methods up to 7% compared to the latest methods. Show more

Keywords: Sentiment analysis, sentiment dictionary, linguistic phenomena, intensifier, intensifier location

DOI: 10.3233/JIFS-202879

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11763-11776, 2021

Authors: Zhang, Duo | Nguang, Sing Kiong | Shu, Lan | Qiu, Dong

Article Type: Research Article

Abstract: This paper focuses on establishing the trilinear fuzzy seepage model with multiple fuzzy parameters for shale gas reservoirs. Different from the conventional seepage models of shale gas reservoirs, the multiple fuzzy parameters seepage model uses fuzzy numbers to describe some parameters with uncertainty. Firstly, the multiple fuzzy parameters seepage model is constructed based on fuzzy concepts. The fuzzy structure element method and the centroid method are used to solve the fuzzy seepage model and defuzzifier, respectively. Secondly, the advantages of the development fuzzy model over the conventional seepage model are discussed and illustrated through numerical examples and simulations. Finally, to …further study the seepage laws inside shale gas reservoirs, this paper explores the sensitivity of relevant main control parameters to gas production based on the development model. Show more

Keywords: Shale gas reservoirs, fuzzy parameter, fuzzy differential equation, fuzzy structural element, fuzzy modeling

DOI: 10.3233/JIFS-202898

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11777-11797, 2021

Authors: Choudhary, Anu | Raj, Kuldip | Mursaleen, M.

Article Type: Research Article

Abstract: Tauberian theorem serves the purpose to recuperate Pringsheim’s convergence of a double sequence from its (C , 1, 1) summability under some additional conditions known as Tauberian conditions. In this article, we intend to introduce some Tauberian theorems for fuzzy number sequences by using the de la Vallée Poussin mean and double difference operator of order r  . We prove that a bounded double sequence of fuzzy number which is Δ u r - convergent is ( C , 1 , 1 ) Δ u r - summable to the …same fuzzy number L  . We make an effort to develop some new slowly oscillating and Hardy-type Tauberian conditions in certain senses employing de la Vallée Poussin mean. We establish a connection between the Δ u r - Hardy type and Δ u r - slowly oscillating Tauberian condition. Finally by using these new slowly oscillating and Hardy-type Tauberian conditions, we explore some relations between ( C , 1 , 1 ) Δ u r - summable and Δ u r - convergent double fuzzy number sequences. Show more

Keywords: Fuzzy number, difference operator, double sequences, Tauberian theorem, (C, 1, 1)- summability

DOI: 10.3233/JIFS-202921

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11799-11808, 2021

Authors: Lei, Fan | Wei, Guiwu | Chen, Xudong

Article Type: Research Article

Abstract: Probabilistic double hierarchy linguistic term set (PDHLTS) can not only express the complex linguistic information that the probabilistic linguistic term set (PLTS) cannot express, but also reflect the frequency or importance of linguistic term set (LTS)that cannot be reflected by the double hierarchy linguistic term set (DHLTS). It is an effective tool to deal with multiple attribute group decision making (MAGDM) problems. Therefore, in this paper, we propose several aggregation operators which can aggregate PDHLTS information and apply them to MAGDM problems. Firstly, the basic notion of PDHLTS is reviewed, and the distance formula and algorithm of PDHLTS are defined; …then, extant weighted averaging (WA) operator, weighted geometric(WG) operator and power weighted averaging (PWA) operator, power weighted geometric(PWG) operator to PDHLTS, and establish probability double hierarchy linguistic weighted averaging (PDHLWA) operator, probability double hierarchy linguistic weighted geometric (PDHLWG) operator, probability double hierarchy linguistic power weighted averaging (PDHLPWA) operator, probability double hierarchy linguistic power weighted geometric (PDHLPWG) operator; in addition, The idempotency, boundedness and monotonicity of these aggregation operators are studied; what’s more, those aggregation operators are proposed to establish the enterprise credit self-evaluation model; Finally, compared with the available probabilistic double hierarchy linguistic MAGDM methods, the defined model is proved to be scientific and effective. Show more

Keywords: Multiple attribute group decision making (MAGDM), probabilistic double hierarchy term set (PDHLTS), aggregation operators, enterprise credit self-evaluation model

DOI: 10.3233/JIFS-202922

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11809-11828, 2021

Authors: Wu, Xinhao | Lu, Qiujun

Article Type: Research Article

Abstract: Application of quantitative methods for forecasting purposes in financial markets has attracted significant attention from researchers and managers in recent years when conventional time series forecasting models can hardly develop the inherent rules of complex nonlinear dynamic financial systems. In this paper, based on the fuzzy technique integrated with the statistical tools and artificial neural network, a new hybrid forecasting system consisting of three stages is constructed to exhibit effectively improved forecasting accuracy of financial asset price. The sum of squared errors is minimized to determine the coefficients in fitting the fuzzy autoregression model stage for formulating sample groups to …deal with data containing outliers. Fuzzy bilinear regression model introducing risk view based on quadratic programming algorithm that reflects the properties of both least squares and possibility approaches without expert knowledge is developed in the second stage. The main idea of the model considers the sub-models tracking the possible relations between the spread and the center, also linking the estimation deviation with risk degree of fitness of the model. In the third stage, fuzzy bilinear regression forecasting combining with the optimal architecture of probabilistic neural network classifiers indicates that the proposed method has great contribution to control over-wide interval financial data with a certain confidence level. Statistical validation and performance analysis using historical financial asset yield series on Shanghai Stock Exchange composite index all exhibit the effectiveness and stability of the proposed hybrid forecasting formulation compared with other forecasting methods. Show more

Keywords: Financial asset yield series forecasting, fuzzy bilinear regression, probabilistic neural network, symmetrical triangular fuzzy number, risk-neutral

DOI: 10.3233/JIFS-202927

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11829-11844, 2021

Authors: Shabir, Muhammad | Mubarak, Asad | Naz, Munazza

Article Type: Research Article

Abstract: The rough set theory is an effective method for analyzing data vagueness, while bipolar soft sets can handle data ambiguity and bipolarity in many cases. In this article, we apply Pawlak’s concept of rough sets to the bipolar soft sets and introduce the rough bipolar soft sets by defining a rough approximation of a bipolar soft set in a generalized soft approximation space. We study their structural properties and discuss how the soft binary relation affects the rough approximations of a bipolar soft set. Two sorts of bipolar soft topologies induced by soft binary relation are examined. We additionally discuss …some similarity relations between the bipolar soft sets, depending on their roughness. Such bipolar soft sets are very useful in the problems related to decision-making such as supplier selection problem, purchase problem, portfolio selection, site selection problem etc. A methodology has been introduced for this purpose and two algorithms are presented based upon the ongoing notions of foresets and aftersets respectively. These algorithms determine the best/worst choices by considering rough approximations over two universes i.e. the universe of objects and universe of parameters under a single framework of rough bipolar soft sets. Show more

Keywords: Rough sets, bipolar soft sets, rough bipolar soft sets, bipolar soft topology, decision making

DOI: 10.3233/JIFS-202958

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11845-11860, 2021

Authors: Zhu, Jia-Nian | Liu, Xu-Chong | Liu, Chong

Article Type: Research Article

Abstract: Non-equidistant non-homogenous grey model (abbreviated as NENGM (1,1, k ) model) is a grey prediction model suitable for predicting time series with non-equal intervals. It is widely used in various fields of society due to its high prediction accuracy and strong adaptability. In order to further improve the prediction accuracy of the NENGM (1,1, k ) model, the NENGM (1,1, k ) model is optimized in terms of the cumulative order and background value of the NENGM (1,1, k ) model, and a NENGM (1,1, k ) model based on double optimization is established (abbreviated as FBNENGM (1,1, k ) …model), and the whale optimization algorithm is used to solve the best parameters of the model. In order to verify the feasibility and validity of the FBNENGM (1,1, k ) model, the FBNENGM (1,1, k ) model and other four prediction models are applied to three cases respectively, and three indexes commonly used to evaluate the performance of prediction models are used to distinguish. The results show that the prediction accuracy of the FBNENGM (1,1, k ) model based on double optimization is better than other prediction models. Show more

Keywords: Grey system theory, fractional-order accumulation, grey prediction model, FBNENGM (1, 1, k) model, ·whale optimization algorithm

DOI: 10.3233/JIFS-210023

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11861-11874, 2021

Authors: Li, Haiyan | Yang, Xiangfeng

Article Type: Research Article

Abstract: Uncertain time series is chronological sequence overtime where each period is described by an uncertain variable. In this paper, we investigate the smoothly clipped absolute deviation (SCAD) penalized estimation method to determine the unknown parameters in the uncertain autoregressive model, and the autoregressive model order can be simultaneously obtained for a pre-given thresholding parameter λ . Besides, an iterative algorithm based on local quadratic approximations for finding the penalized estimators is provided. Based on the fitted autoregressive model, the forecast value and the future value’s confidence interval are given. Besides, the sum of the squared error approach to select the …optimal λ is discussed. Finally, some examples are used to validate the effectiveness of the proposed method by the comparative analysis. Show more

Keywords: Uncertain variable, uncertain autoregressive model, SCAD penalty

DOI: 10.3233/JIFS-210031

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11875-11885, 2021

Authors: Bashir, Humera | Zahid, Zohaib | Kashif, Agha | Zafar, Sohail | Liu, Jia-Bao

Article Type: Research Article

Abstract: The 2-metric resolvability is an extension of metric resolvability in graphs having several applications in intelligent systems for example network optimization, robot navigation and sensor networking. Rotationally symmetric graphs are important in intelligent networks due to uniform rate of data transformation to all nodes. In this article, 2-metric dimension of rotationally symmetric plane graphs R n , S n and T n is computed and found to be independent of the number of vertices.

Keywords: 2-metric dimension, rotationally symmetric, plane graphs

DOI: 10.3233/JIFS-210040

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11887-11895, 2021

Authors: Chen, Lei | Han, Jun | Tian, Feng

Article Type: Research Article

Abstract: Infrared (IR) images can distinguish targets from their backgrounds based on difference in thermal radiation, whereas visible images can provide texture details with high spatial resolution. The fusion of the IR and visible images has many advantages and can be applied to applications such as target detection and recognition. This paper proposes a two-layer generative adversarial network (GAN) to fuse these two types of images. In the first layer, the network generate fused images using two GANs: one uses the IR image as input and the visible image as ground truth, and the other with the visible as input and …the IR as ground truth. In the second layer, the network transfer one of the two fused images generated in the first layer as input and the other as ground truth to GAN to generate the final fused image. We adopt TNO and INO data sets to verify our method, and by comparing with eight objective evaluation parameters obtained by other ten methods. It is demonstrated that our method is able to achieve better performance than state-of-arts on preserving both texture details and thermal information. Show more

Keywords: IR and visible images, image fusion, generative adversarial network, deep learning

DOI: 10.3233/JIFS-210041

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11897-11913, 2021

Authors: Zhang, Shao-Yu

Article Type: Research Article

Abstract: This paper introduces a special Galois connection combined with the wedge-below relation. Furthermore, by using this tool, it is shown that the category of M -fuzzifying betweenness spaces and the category of M -fuzzifying convex spaces are isomorphic and the category of arity-2 M -fuzzifying convex spaces can be embedded in the category of M -fuzzifying interval spaces as a reflective subcategory.

Keywords: Fuzzy convex structure, fuzzy betweenness space, fuzzy interval space, arity-2 fuzzy convexity

DOI: 10.3233/JIFS-210060

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11915-11925, 2021

Authors: Oh, Ju-Mok | Kim, Yong Chan

Article Type: Research Article

Abstract: In this paper, we introduce the notions of join preserving maps using distance spaces instead of fuzzy partially ordered sets on complete co-residuated lattices. We investigate the properties of Alexandrov fuzzy topologies, distance functions, join preserving maps and upper approximation operators. Furthermore, we study their relations and examples. We prove that there exist isomorphic categories and Galois correspondences between their categories.

Keywords: Complete co-residuated lattices, distance functions, join preserving maps, upper approximation operators, Alexandrov fuzzy topologies

DOI: 10.3233/JIFS-210061

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11927-11939, 2021

Authors: Chen, Xiaojun | Jia, Shengbin | Ding, Ling | Xiang, Yang

Article Type: Research Article

Abstract: Knowledge graph reasoning or completion aims at inferring missing facts by reasoning about the information already present in the knowledge graph. In this work, we explore the problem of temporal knowledge graph reasoning that performs inference on the graph over time. Most existing reasoning models ignore the time information when learning entities and relations representations. For example, the fact (Scarlett Johansson , spouse Of , Ryan Reynolds ) was true only during 2008 - 2011. To facilitate temporal reasoning, we present TA-TransRILP , which involves temporal information by utilizing RNNs and takes advantage of Integer Linear Programming. Specifically, we …utilize a character-level long short-term memory network to encode relations with sequences of temporal tokens, and combine it with common reasoning model. To achieve more accurate reasoning, we further deploy temporal consistency constraints to basic model, which can help in assessing the validity of a fact better. We conduct entity prediction and relation prediction on YAGO11k and Wikidata12k datasets. Experimental results demonstrate that TA-TransRILP can make more accurate predictions by taking time information and temporal consistency constraints into account, and outperforms existing methods with a significant improvement about 6-8% on Hits@10. Show more

Keywords: Knowledge graph reasoning, temporal information, temporal consistency constraints, integer linear programming

DOI: 10.3233/JIFS-210064

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11941-11950, 2021

Authors: Yu, Junqi | Zhang, Tianlun | Zhao, Anjun | Xie, Yunfei

Article Type: Research Article

Abstract: Energy consumption prediction can provide reliable data support for energy scheduling and optimization of office buildings. It is difficult for traditional prediction model to achieve stable accuracy and robustness when energy consumption mode is complex and data sources are diverse. Based on such situation, this paper raised an approach containing the method of comprehensive similar day and ensemble learning. Firstly, the historical data was analyzed and calculated to obtain the similarity degree of meteorological features, time factor and precursor. Next, the entropy weight method was used to calculate comprehensive similar day and applied to the model training. Then the improved …sine cosine optimization algorithm (SCA) was applied to the optimization and parameter selection of a single model. Finally, an approach of model selection and integration based on dominance was proposed, which was compared with Support Vector Regression (SVR), Back Propagation Neural Network (BPNN), Long Short-Term Memory (LSTM), with a large office building in Xi ‘an taken as an example to analysis showing that compared with the prediction accuracy, root mean square percentage error (RMSPE) in the ensemble learning model after using comprehensive similar day was reduced by about 0.15 compared with the BP model, and was reduced by about 0.05, 0.06 compared with the SVR and LSTM model. Respectively, the mean absolute percentage error (MAPE) was reduced by 12.02%, 6.51% and 5.28%. Compared with several other integration methods, integration model based on dominance reduced absolute error at all times. Accordingly, the proposed approach can effectively solve problems of low accuracy and poor robustness in traditional model and predict the building energy consumption efficaciously. Show more

Keywords: Similar day, ensemble learning, sine cosine optimization algorithm, energy consumption prediction

DOI: 10.3233/JIFS-210069

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11951-11965, 2021

Authors: Wu, Meiqin | Li, Zhuoyu | Fan, Jianping

Article Type: Research Article

Abstract: With resource shortage and environmental pollution becoming more and more serious, the development of new energy vehicles (NEVs) plays an important role. In this paper, the hybrid method of best-worst method (BWM), Multi-Objective Optimization by Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), and Evaluation based on Distance from Average Solution (EDAS) is used to evaluate new energy vehicles (NEVs) and select the best new energy vehicle. BWM method is used to obtain the subjective preference weight, MULTIMOORA method is used to integrate the objective data with the subjective weight to evaluate new energy vehicles, and the final ranking of alternatives …is obtained by the EDAS method. The paper collect the data of 22 representative new energy vehicle types in China, the validity and feasibility of the method is verified. Show more

Keywords: Best-worst method, multi-objective optimization by ratio analysis plus full multiplicative form, evaluation based on distance from average solution, new energy vehicles

DOI: 10.3233/JIFS-210074

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11967-11980, 2021