Journal of Intelligent & Fuzzy Systems - Volume 38, issue 4

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 3999-3999, 2020

Authors: Liu, Peide | Li, Ying

Article Type: Research Article

Abstract: The intuitionistic linguistic (IL) variable (ILV) can express the vague and uncertain information in a better way, and the partitioned Heronian mean (PHM) operator can group attributes that have relationships with each other into one zone and the independent attributes are in different zones, so in this paper, we will propose some new PHM operators for IL information (ILI) and then apply them to multiple attribute group decision-making (MAGDM). Firstly, the some improved operational rules for ILVs are developed, which can provide a more accurate result and avoid the loss of information, then we extend the PHM operator to the …IL environment and propose the intuitionistic linguistic partitioned Heronian mean (ILPHM) operator and the intuitionistic linguistic weighted partitioned Heronian mean (ILWPHM) operator, which can fully consider the advantages of the ILI and the PHM operator. Meanwhile, we discuss some desirable properties and special cases of the two operators. Further, we develop the MAGDM approach with ILI based on the developed operators. Lastly, a numerical instance is given to verify the feasibility and the superiority of the proposed method. Show more

Keywords: Intuitionistic linguistic information, PHM, MAGDM

DOI: 10.3233/JIFS-181175

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4001-4029, 2020

Authors: Lu, Yanling | Xu, Yejun | Qu, Shaojian | Xu, Zeshui | Ma, Gang | Li, Ziwei

Article Type: Research Article

Abstract: In multiattribute decision making problem, it is usually that the opinions of agent may be influenced by close friends or people with similar interests among his social network. This situation could act on the evaluation process of agent toward candidates, thereby affecting the overall two-sided matching results. This paper proposes a framework based on social network analysis. It can effectively achieve multiattribute social network matching that the relative weights of influencers are unknown before. In the proposed framework, the complete trust assessment matrix can be obtained through depicting the trust propagation relationship between agent and influencers. According to the trust …assessment result, a nonlinear optimization model is developed to calculate the unknown weights of influencers, and then the obtained weights of influencers are integrated into the two-sided evaluation process. Furthermore, two multi-objective optimization models are constructed to manage the rational agents and conservative agents. Based on the multi-objective optimization models, we generate the optimal matching pairs. Finally, detailed comparison analysis and discussion are presented to check the effectiveness of the proposed social network matching method. Show more

Keywords: Multiattribute matching decision making, social network analysis, optimization model, risk preference

DOI: 10.3233/JIFS-182535

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4031-4048, 2020

Authors: Ramadan, A.A. | Kim, Y.C. | Elkordy, E.H.

Article Type: Research Article

Abstract: In this paper, we investigate the relations between the L -fuzzy pre-proximities, L -fuzzy interior operators and L -fuzzy topological spaces in complete residuated lattices. In addition, degrees of L -fuzzy continuity, L -fuzzy proximity and L -fuzzy interior mappings are proposed and their connections are studied. Also, we show that there is a Galois correspondence between the category of separated L -fuzzy interior spaces and that of separated L -fuzzy pre-proximity spaces. Finally, we give their examples.

Keywords: Complete residuated lattice, L-fuzzy pre-proximity, L-fuzzy interior operators, Galois correspondence

DOI: 10.3233/JIFS-182652

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4049-4060, 2020

Authors: Yanmaz, Ozgur | Turgut, Yakup | Can, Emine Nisa | Kahraman, Cengiz

Article Type: Research Article

Abstract: Classical multi-criteria decision making (MCDM) methods have been extended to their fuzzy versions under uncertainty in the literature. Besides, these ordinary fuzzy MCDM methods have been further extended to their new versions through the recently developed types of ordinary fuzzy sets. This study extends the evaluation based on distance from the average solution (EDAS) method by using interval-valued Pythagorean fuzzy numbers to solve fuzzy multi-criteria group decision- making problems with a larger membership domain providing more flexibility. An illustrative example of the car selection problem is given to show the effectiveness and applicability of the proposed model and results are …compared with intuitionistic interval-valued fuzzy EDAS method. A sensitivity analysis is also performed to reveal the effect of the weights on alternative rankings. Show more

Keywords: EDAS, pythagorean, fuzzy, car selection

DOI: 10.3233/JIFS-182667

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4061-4077, 2020

Authors: Sánchez, Daniel Eduardo | Esmi, Estevão | de Barros, Laécio Carvalho | Miebach, Alessandro Donadio | Cecconello, Moiseis dos Santos

Article Type: Research Article

Abstract: In this manuscript, we present numerical solutions of a p -fuzzy system that models the Goodwin economic cycle. This model describes the dynamic interaction between labour share and the employment rate in an economy. One can use p -fuzzy systems to obtain solutions for differential equations whose the vector field are uncertain and partially known. The proposed p -fuzzy system is based on a fuzzy rule-based systems whose fuzzy rules represent economic premises described in the Goodwin model. We use two approaches to adjust the fuzzy terms of the corresponding fuzzy rule base from the economical data of a given …country. The first approach is based on statical measures and the second one uses fuzzy c-means clustering method. Finally, we test our proposal to estimate the growth cycles of the labour share and the employment rate of Germany and we compare the obtained results with the historical data. Show more

Keywords: P-fuzzy systems, Goodwin model, fuzzy rules, fuzzy numbers, fuzzy c-means

DOI: 10.3233/JIFS-182762

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4079-4090, 2020

Authors: Li, Jingmei | Wu, Weifei | Xue, Di

Article Type: Research Article

Abstract:  Transfer learning is a new machine learning algorithm. It solves problems in different but related target domains by utilizing the knowledge in existing data. Based on the classical SVM algorithm and transfer learning, a selective transfer learning support vector machine (STL-SVM) algorithm is proposed in this paper. First, STL-SVM uses the maximum mean discrepancy to measure the weight vector of the source domain samples relative to the target domain, and selects samples from the source domain according to each weight to avoid negative transfer. Then, the knowledge in the source domain is learned by the approximate extreme point support vector …at the minimum training data cost. Finally, the object function is constructed by the obtained knowledge and the soft-margin SVM. In the constraint conditions of the objective function, the learned knowledge that is highly correlated with the target domain is selected, and further, the phenomenon of negative transfer is avoided in principle. STL-SVM solves the problem of negative transfer, and has considerable advantages in training time efficiency compared with the existing algorithms. The experimental results on artificial and real datasets show the effectiveness of the proposed algorithm. Show more

Keywords: Machine learning, support vector machine, transfer learning, classification

DOI: 10.3233/JIFS-190055

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4091-4106, 2020

Authors: Sae-Ueng, Pannipa | Skrbic, Srdjan

Article Type: Research Article

Abstract: In recent years, there has been an increased interest in processing fuzzy queries over XML data that is also possibly fuzzy. Attention has been paid to various extensions of XML query languages that introduce concepts of fuzzy theory. We propose an extension of the XQuery query language in an attempt to handle flexible queries that provide priority, threshold, and fuzzy expression as well as fuzzy linguistic labels allowing users great flexibility in customizing query constraints. We give a detailed description of an advanced query processing software system developed using GPFCSP (Generalized Prioritized Fuzzy Constraint Satisfaction Problem) as the theoretical background. …The software, called FXI (Fuzzy XQuery Interpreter), was developed as a web application using Java, AngularJS, and eXist-db — an open source native XML database and it incorporates various advanced features such as fuzzy ordering operations and fuzzy compatibility calculations that includes priorities. The paper presents its design, the most important considerations related to implementation, as well as testing using realistic scenarios. Show more

Keywords: Fuzzy XQuery, XQuery Interpreter, XQuery, XML Database

DOI: 10.3233/JIFS-190202

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4107-4118, 2020

Authors: Yang, Xiangfeng | Ni, Yaodong

Article Type: Research Article

Abstract:  Along with increasing and extension of uncertain set theory in decision making, ordering and ranking of uncertain sets have significantly become relevant, that is, an uncertain set needs to be evaluated and compared with the others. This paper introduces the size relation between two uncertain sets. It derives a formula to calculate the uncertain measure that an uncertain set is less than or equal to another one. Moreover, some examples are given to illustrate the size relation of uncertain sets. Finally, clustering is proposed as an application.

Keywords: Uncertainty theory, uncertain set, membership function, size relation, clustering

DOI: 10.3233/JIFS-190342

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4119-4125, 2020

Authors: Murillo, Javier | Guillaume, Serge | Sari, Tewfik | Bulacio, Pilar

Article Type: Research Article

Abstract:  Fuzzy measures are used for modeling interactions between a set of elements. Simplified fuzzy measures, as k -maxitive measures, were proposed in the literature for complexity and semantic considerations. In order to analyze the importance of a coalition in the fuzzy measure, the use of indices is required. This work focuses on the generalized interaction index, gindex . Its computation requires many resources in both time and space. Following the efforts to reduce the complexity of fuzzy measure identification, this work presents two algorithms to compute the gindex for k -maxitive measures. The structure of k -maxitive measures makes …possible to compute the gindex considering the coalitions at level k and, for each of them, the number of coalitions sharing the same coefficient (called inheritors). The first algorithm deals with the space complexity and the second one also optimizes the runtime by not generating, but only counting, the number of inheritors. While counting the number of descendants is easy, this is not the case for the number of inheritors due to all the inheritors of previous considered coalitions have to be taken into account. The two proposed algorithms are tested with synthetic k -maxitive measures showing that the second algorithm is around 4 times faster than the first one. Show more

Keywords: Fuzzy measures, Shapley index, interaction index, k-maxitive measures

DOI: 10.3233/JIFS-190403

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4127-4137, 2020