University of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190601cover Vol.16,no.3- June 201901463910.22111/ijfs.2019.4639ENJournal Article20190513https://ijfs.usb.ac.ir/article_4639_eaead6ff45d62684779be81bcead2780.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Properties of fuzzy relations and aggregation process in decision making115464010.22111/ijfs.2019.4640ENU.BentkowskaInterdisciplinary Centre for Computational Modelling, University of Rzeszow, Al. Rejtana 16C, 35-959 Rzeszow, PolandJournal Article20170713In this contribution connections between input fuzzy relations R<sub>1</sub>, . . . ,R<sub>n</sub> on a set <em>X</em> and the output fuzzy relation<br />R<sub>F</sub> = F(R<sub>1</sub>, . . . ,R<sub>n</sub>) are studied. F is a function of the form F : [0, 1]<sup>n</sup> → [0, 1] and R<sub>F</sub> is called an aggregated fuzzy<br />relation. In the literature the problem of preservation, by a function <em>F</em>, diverse types of properties of fuzzy relations<br />R<sub>1</sub>, . . . ,R<sub>n</sub> is examined. Here, it is considered the converse approach. Namely, fuzzy relation R<sub>F</sub> = F(R<sub>1</sub>, . . . ,R<sub>n</sub>) is<br />assumed to have a given property and then it is checked if fuzzy relations R<sub>1</sub>, . . . ,R<sub>n</sub> have this property. Moreover, a<br />discussion on the mentioned two approaches is provided. The properties, which are examined in this paper, depend on<br />their notions on binary operations B : [0, 1]<sup>2</sup> → [0, 1]. By incorporating operation B these properties are generalized<br />versions of known properties of fuzzy relations.https://ijfs.usb.ac.ir/article_4640_dc4adb5c9a4cc97602f04fd3e6fcdcb3.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629A fuzzy reasoning method based on compensating operation and its application to fuzzy systems1734464110.22111/ijfs.2019.4641ENS. I.KwakCollege of Information Science, Kim Il Sung University, Pyongyang 999093, D P R of KoreaU. S.RyuScience of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, ChinaG. J.KimCollege of Information Science, Kim Il Sung University, Pyongyang 999093, D P R of KoreaM. H.JoCollege of Information Science, Kim Il Sung University, Pyongyang 999093, D P R of KoreaJournal Article20180313In this paper, we present a new fuzzy reasoning method based on the compensating fuzzy reasoning (CFR). Its basic<br />idea is to obtain a new fuzzy reasoning result by moving and deforming the consequent fuzzy set on the basis of the<br />moving, deformation, and moving-deformation operations between the antecedent fuzzy set and observation information.<br />Experimental results on real-world data sets show that proposed method significantly improve the accuracy and time<br />performance of fuzzy neural network learning.https://ijfs.usb.ac.ir/article_4641_847b3e445a34261dcebf60f8e902e139.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Determining appropriate weight for criteria in multi criteria group decision making problems using an Lp model and similarity measure3546464310.22111/ijfs.2019.4643ENZ.EslaminasabDepartment of Mathematics, Kerman Branch, Islamic Azad University, Kerman, IranA.HamzeheeDepartment of Mathematics, Kerman Branch, Islamic Azad University, Kerman, IranJournal Article20180113Decision matrix in group decision making problems depends on a lot of criteria. It is essential to know the necessity of<br />weight or coefficient of each criterion. Accurate and precise selection of weight will help to achieve the intended goal.<br />The aim of this article is to introduce a linear programming model for recognizing the importance of each criterion in<br />multi criteria group decision making with intuitionistic fuzzy data through similarity measure between each alternative<br />and ideal alternative. Based on this model, decision makers and experts will be prevented from making mistakes in<br />recognizing the weight and shape of standardization of their mental measurement units. By using of determined weights,<br />the alternatives will be ranked according to a new method based on ELECTRE III method. An applied and numerical<br />example is presented and the obtained results are compared with other methods.https://ijfs.usb.ac.ir/article_4643_167d3c65d73d5359950a777b8f2bdf3c.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Refueling problem of alternative fuel vehicles under intuitionistic fuzzy refueling waiting times: a fuzzy approach4762464410.22111/ijfs.2019.4644ENF.FerdowsiFaculty of Mathematics, Shiraz University of Technology, Shiraz, IranH. R.MalekiFaculty of Mathematics, Shiraz University of Technology, Shiraz, IranS.NiroomandDepartment of Industrial Engineering, Firouzabad Institute of Higher Education, Firouzabad, Fars, IranJournal Article20180313Using alternative fuel vehicles is one of the ways to reduce the consumption of fossil fuels which have many negative environmental effects. An alternative fuel vehicle needs special planning for its refueling operations because of some reasons, e.g. limited number of refueling stations, uncertain refueling queue times in the stations, variable alternative fuel prices among the stations, etc. In this paper, a new problem as refueling an alternative fuel vehicle on a given path is formulated to minimize the cost of refueling and waiting times in the stations for refueling operations, simultaneously. To be more close to real-world situations, the waiting times are considered as intuitionistic fuzzy numbers in order to reflect uncertainty as well as hesitation due to various uncontrollable factors. To cope with the uncertainty of the problem, an intuitionistic fuzzy chance constrained method based on credibility measure is proposed to convert the fuzzy formulation to a crisp model. In order to tackle the bi-objective crisp formulation, a new interactive fuzzy solution method is proposed. A computational study on a real case from Turkey shows that the performance of the presented method is either better or the same as the approaches of the literature.<br />}https://ijfs.usb.ac.ir/article_4644_1f94e63243159a2429dd6d412999e583.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Scattered data approximation of fully fuzzy data by quasi-interpolation6372464510.22111/ijfs.2019.4645ENK.ShakibiDepartment of Mathematics, Central Tehran Branch, Islamic Azad University, Tehran, IranM.AmirfakhrianDepartment of Mathematics, Central Tehran Branch, Islamic Azad University, Tehran, IranE. J.KansaConvergent Solutions, LLC, Livermore, CA, USA.Journal Article20170413Fuzzy quasi-interpolations help to reduce the complexity of solving a linear system of equations compared with fuzzy interpolations. Almost all fuzzy quasi-interpolations are focused on the form of $\widetilde{f}^{*}:\mathbb{R}\rightarrow F(\mathbb{R})$ or $\widetilde{f}^{*}:F(\mathbb{R})\rightarrow \mathbb{R}$. In this paper, we intend to offer a novel fuzzy radial basis function by the concept of source distance. Then, we will construct a fuzzy linear combination of such basis functions in order to introduce a fully fuzzy quasi-interpolation in the form of $\widetilde{f}^{*}:F(\mathbb{R})\rightarrow F(\mathbb{R})$. Also the error estimation of the proposed method is proved in terms of the fully fuzzy modulus of continuity which will be introduced in this paper. Finally some examples have been given to emphasize the acceptable accuracy of our method.https://ijfs.usb.ac.ir/article_4645_60187389011459142e156614567ad4e0.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Categories of lattice-valued closure (interior) operators and Alexandroff L-fuzzy topologies7384464610.22111/ijfs.2019.4646ENA. A.RamadanDepartment of Mathematics, Faculty of Science, Beni-Suef University, Beni-Suef, EgyptL.LiDepartment of Mathematics, Liaocheng University, Liaocheng, 252059 P.R. China and College of Mathematics and Systems
Science, Shandong University of Science and Technology, Qingdao 266590, P.R.China.Journal Article20170613Galois connection in category theory play an important role in<br />establish the relationships between different spatial structures. In<br />this paper, we prove that there exist many interesting Galois<br />connections between the category of Alexandroff $L$-fuzzy<br />topological spaces, the category of reflexive $L$-fuzzy<br />approximation spaces and the category of Alexandroff $L$-fuzzy<br />interior (closure) spaces. This indicates that there is a close<br />connection between the three structures.https://ijfs.usb.ac.ir/article_4646_2118d60fe9f7717e282848084f4e62c2.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629A modified position value for communication situations and its fuzzification8596464710.22111/ijfs.2019.4647ENX. H.LiDepartment of Mathematics, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, PR ChinaH.SunDepartment of Mathematics, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, PR ChinaG. J.XuDepartment of Mathematics, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, PR ChinaJournal Article20170714Myerson treated various situations of cooperation in the field of cooperative games and proposed the communication structure. In this paper, we define and characterize an allocation rule in terms of the position value, called an average spanning tree solution, for communication situations by introducing a concept of cooperation relationship which says that two players are deemed to possess this relationship if there is a communication path through them. Considering the fact that the extent to what players participate in a coalition may be partially restricted for uncertain possibilities, we construct a graph game in multilinear extension form and continue to explore the fuzzy average spanning tree solution on a framework of communication situation with fuzzy coalition.https://ijfs.usb.ac.ir/article_4647_539ca614c35151fcec95d77cea189993.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Multiple attribute decision making with triangular intuitionistic fuzzy numbers based on zero-sum game approach97112464810.22111/ijfs.2019.4648ENJ.XuCollege of Modern Economics & Management, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaJ. Y.DongSchool of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaS. P.WanCollege of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaJ.GaoCollege of Modern Economics & Management, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaJournal Article20171214For many decision problems with uncertainty, triangular intuitionistic fuzzy number is a useful tool in expressing ill-known quantities. This paper develops a novel decision method based on zero-sum game for multiple attribute decision making problems where the attribute values take the form of triangular intuitionistic fuzzy numbers and the attribute weights are unknown. First, a new value index is defined for triangular intuitionistic fuzzy numbers on the basis of the centroid. Thereby, a new ranking approach is presented for comparing triangular intuitionistic fuzzy numbers. We formulate a multiple attribute decision making problem as a two-person zero-sum game with payoffs of triangular intuitionistic fuzzy numbers. Then, following the new ranking approach, the fuzzy matrix game is converted as a pair of crisp linear programming models, and the optimal strategies are objectively derived by solving such models. Therefore, the ranking order of alternatives is determined by the expected scores of alternatives. An example of video monitoring system selection is demonstrated to illustrate the effectiveness of the proposed methodology.https://ijfs.usb.ac.ir/article_4648_daf23e3b6bfac37b93060d338d1358e8.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629A new vector valued similarity measure for intuitionistic fuzzy sets based on OWA operators113126464910.22111/ijfs.2019.4649ENL.FeiInstitute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, 610054,
ChinaH.WangSchool of Computer and Information Sciences,Southwest University, Chongqing 400715, ChinaL.ChenSchool of Computer and Information Sciences,Southwest University, Chongqing 400715, ChinaY.DengInstitute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, 610054,
ChinaJournal Article20160414Plenty of researches have been carried out, focusing on the measures of distance, similarity, and correlation between intuitionistic fuzzy sets (IFSs).<br />However, most of them are single-valued measures and lack of potential for efficiency validation.<br />In this paper, a new vector valued similarity measure for IFSs is proposed based on OWA operators.<br />The vector is defined as a two-tuple consisting of the similarity measure and uncertainty measure, in which the latter is the uncertainty of the former.<br />OWA operators have the ability to aggregate all values in the universe of discourse of IFSs, and to determine the weights according to specific applications.<br />A framework is built to measure similarity between IFSs.<br />A series of definitions and theorems are given and proved to satisfy the corresponding axioms defined for IFSs.<br />In order to illustrate the effectiveness of the proposed vector valued similarity measure,<br />a classification problem is used as an application.https://ijfs.usb.ac.ir/article_4649_2068262d491a0b62c117fd72a42d86e4.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Decentralized prognosis of fuzzy discrete-event systems127143465010.22111/ijfs.2019.4650ENB.BenmessahelComputer Science Department, University of Ferhat Abbas Setif 1, Pole 2 - El Bez, 19000 Setif, AlgeriaM.TouahriaComputer Science Department, University of Ferhat Abbas Setif 1, Pole 2 - El Bez, 19000 Setif, AlgeriaF.NouiouaAix-Marseille University, CNRS, ENSAM, University of Toulon, LSIS UMR 7296, Marseille, FranceJ.GaberComputer Science Department, Universite de Technologie de Belfort Montbeliard, Rue Thierry Mieg, 90010 Belfort, FranceP.LorenzComputer Science Department, IUT, University of Haute Alsace, Colmar, FranceJournal Article20170114This paper gives a decentralized approach to the problem of failure prognosis in the framework of fuzzy discrete event systems (FDES). A notion of co-predictability is formalized for decentralized prognosis of FDESs, where several local agents with fuzzy observability rather than crisp observability are used in the prognosis task. An FDES is said to be co-predictable if each faulty event can be predicted prior to its occurrence by at least one local agent using the observability of fuzzy events. The verification of the decentralized predictability is performed by constructing a fuzzy co-verifier from a given FDES. The complexity of the fuzzy co-verifier is polynomial with respect to the FDES being predicted, and is exponential with respect to the number of the local prognosis agents. Then, a necessary and sufficient condition for the co-predictability of FDESs is given. In addition, we show that the proposed method may be used to deal with the decentralized prognosis for both FDESs and crisp DESs. Finally, to illustrate the effectiveness of the approach, some examples are provided.https://ijfs.usb.ac.ir/article_4650_1ce8ab4640284f082ad9c427c7cac04a.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629A new method for solving fuzzy multi-objective linear programming problems145159465110.22111/ijfs.2019.4651ENJiuyingDongJiangxi University of Finance and EconomicsShupingWanJiangxi University of Finance and EconomicsJournal Article20170714The purpose of this paper is to develop a new two-stage method for fuzzy multi-objective linear program and apply to engineering project portfolio selection. In the fuzzy multi-objective linear program, all the objective coefficients, technological coefficients and resources are trapezoidal fuzzy numbers (TrFNs). An order relationship for TrFNs is introduced by using the interval expectation of TrFNs. In the first stage, the fuzzy multi-objective linear program with TrFNs is transformed into an interval multi-objective linear program according to the order relationship of TrFNs. Combining the ranking order relation between intervals with the satisfactory crisp equivalent forms of interval inequality relations, the interval multi-objective linear program is further transformed into a crisp multi-objective linear program. In the second stage, the positive and negative ideal solutions are calculated as well as the closeness degrees from the positive ideal solution to all objectives on the basis of the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Then, using the closeness degrees, we convert the crisp multi-objective linear program into mono-objective program to solve. The proposed method is not only mathematically rigorous, but also can adequately consider the acceptance degree of decision maker that the fuzzy constraints may be violated. The other possible cases of the fuzzy multi-objective linear program are also discussed. The proposed method is illustrated by means of a project portfolio selection problem.https://ijfs.usb.ac.ir/article_4651_50e95720bca9b0d95d2066979cdfa1d5.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629An efficient approach for availability analysis through fuzzy differential equations and particle swarm optimization161173465210.22111/ijfs.2019.4652ENN.SinghalDepartment of Mathematics, Indian Institute of Technology, Roorkee, IndiaS. P.SharmaDepartment of Mathematics, Indian Institute of Technology, Roorkee, IndiaJournal Article20170814This article formulates a new technique for behavior analysis of systems through fuzzy Kolmogorov's differential equations and Particle Swarm Optimization. For handling the uncertainty in data, differential equations have been formulated by Markov modeling of system in fuzzy environment. First solution of these derived fuzzy Kolmogorov's differential equations has been found by Runge-Kutta fourth order method and thereafter the solution has been improved by Particle Swarm Optimization. Fuzzy availability is estimated in its transient as well as steady states. Sensitivity analysis has also been done to find the relative importance of a particular component of the system. Butter oil processing plant as an industrial system has been studied as a case for application of the proposed approach.https://ijfs.usb.ac.ir/article_4652_2b384bd61bf038f5800625a429428280.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Quantale-valued fuzzy Scott topology175188465310.22111/ijfs.2019.4653ENS. E.HanDepartment of Mathematics Education, Institute of Pure and Applied Mathematics, Chonbuk National University, Jeonju-City
Jeonbuk, 561-756, Republic of KoreaL. X.LuDepartment of Mathematics, College of Natural Science, Chonbuk National University, Jeonju-City Jeonbuk, 561-756, Republic of Korea and School of Mathematics and Science, Hebei GEO University, Shijiazhuang 050018, ChinaW.YaoSchool of Sciences, Hebei University of Science and Technology, Shijiazhuang 050018, P.R. ChinaJournal Article20171214The aim of this paper is to extend the truth value table of<br />lattice-valued convergence spaces to a more general case and<br />then to use it to introduce and study the quantale-valued fuzzy Scott<br />topology in fuzzy domain theory. Let $(L,*,\varepsilon)$ be a<br />commutative unital quantale and let $\otimes$ be a binary operation<br />on $L$ which is distributive over nonempty subsets. The quadruple<br />$(L,*,\otimes,\varepsilon)$ is called a generalized GL-monoid if<br />$(L,*,\varepsilon)$ is a commutative unital quantale and the operation $*$ is<br />$\otimes$-semi-distributive. For generalized GL-monoid $L$ as the<br />truth value table, we systematically propose the stratified<br />$L$-generalized convergence spaces based on stratified $L$-filters,<br />which makes various existing lattice-valued convergence spaces as<br />special cases. For $L$ being a commutative unital quantale, we<br />define a fuzzy Scott convergence structure on $L$-fuzzy dcpos and<br />use it to induce a stratified $L$-topology. This is the inducing way<br />to the definition of quantale-valued fuzzy Scott topology, which<br />seems an appropriate way by some results.https://ijfs.usb.ac.ir/article_4653_f35a750118ba0d313c54fcda469befe8.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190629Fuzzy transferable-utility games: a weighted allocation and related results189197465410.22111/ijfs.2019.4654ENY. H.LiaoDepartment of Applied Mathematics, National Pingtung University, Pingtung 900, TaiwanL. Y.ChungLing-Yun Chung (corresponding author), Graduate School of Technological and Vocational Education, National Yunlin
University of Science and Technology, Yunlin 64002, TaiwanJournal Article20171114By considering the supreme-utilities among fuzzy sets and the weights among participants simultaneously, we introduce the supreme-weighted value on fuzzy transferable-utility games. Further, we provide some equivalent relations to characterize the family of all solutions that admit a potential on weights. We also propose the dividend approach to provide alternative viewpoint for the potential approach. Based on these equivalent relations, several axiomatic results are also proposed to present the rationality for the supreme-weighted value.https://ijfs.usb.ac.ir/article_4654_8bcdf94afd2141fbb8b83df5c4a8fd48.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065416320190601Persian-translation Vol.16, No.3, June 2019201214466310.22111/ijfs.2019.4663ENJournal Article20190522https://ijfs.usb.ac.ir/article_4663_013633a946af48ccd9ec1bb1b9706474.pdf