Results 281 to 290 of about 43,297 (342)
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IEEE Transactions on Fuzzy Systems, 2006
Type-2 fuzzy sets are a generalization of the ordinary fuzzy sets in which each type-2 fuzzy set is characterized by a fuzzy membership function. In this paper, we consider the problem of ranking a set of type-2 fuzzy numbers. We adopt a statistical viewpoint and interpret each type-2 fuzzy number as an ensemble of ordinary fuzzy numbers.
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Type-2 fuzzy sets are a generalization of the ordinary fuzzy sets in which each type-2 fuzzy set is characterized by a fuzzy membership function. In this paper, we consider the problem of ranking a set of type-2 fuzzy numbers. We adopt a statistical viewpoint and interpret each type-2 fuzzy number as an ensemble of ordinary fuzzy numbers.
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Ranking fuzzy numbers with extended fuzzy preference relation
2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236), 2002The crux of the paper is to propose a new ranking method based on a preference relation which is not only easy to compute but also preserving some good properties such as additivity. First, we extend the definition of fuzzy preference relation so that the degree of preference is not confined within 0 and 1.
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New method for ranking fuzzy numbers
The 2nd International Conference on Information Science and Engineering, 2010In this paper, the fragmentation of fuzzy numbers is defined as new sort indicators Based on the Centroid and fragmentation of fuzzy numbers, paper proposes a new ranking method of fuzzy numbers which can overcome the shortcomings of some ranking method to some degree. At last, paper illustrates the practicability of the proposed method by the analysis
null Fan-Hui Zeng, null Jun Cao
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New ranking methods of intuitionistic fuzzy numbers and Pythagorean fuzzy numbers
2020 Chinese Control And Decision Conference (CCDC), 2020The ranking method can distinguish the size of intuitionistic fuzzy numbers and Pythagorean fuzzy numbers, and plays an important role in the application of intuitionistic fuzzy sets and Pythagorean fuzzy sets. Based on the summary of classic ranking methods, this paper proposes some new ranking methods.
Zhang Qiang +4 more
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Note on ranking fuzzy triangular numbers
International Journal of Intelligent Systems, 1998This paper deals with the problem of ranking a set of alternatives, represented by triangular fuzzy numbers, in decision-making situations. Three new methods are proposed, and a notion of preference between alternatives is suggested. A comparison with other methods is provided in the concluding table. © 1998 John Wiley & Sons, Inc.
FACCHINETTI, Gisella +2 more
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On ranking fuzzy numbers using valuations
International Journal of Intelligent Systems, 1999Summary: The importance as well as the difficulty of the problem of ranking fuzzy numbers is pointed out. Here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers.
Yager, Ronald R., Filev, Dimitar
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2015 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) held jointly with 2015 5th World Conference on Soft Computing (WConSC), 2015
Recently we found all the effective ranking indices defined on the set of trapezoidal fuzzy numbers in respect to the axioms of Wang and Kerre. We extend the results for the case of L-R fuzzy numbers and, in addition, we formulate several problems which could complete the present results.
Adrian I. Ban, Lucian Coroianu
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Recently we found all the effective ranking indices defined on the set of trapezoidal fuzzy numbers in respect to the axioms of Wang and Kerre. We extend the results for the case of L-R fuzzy numbers and, in addition, we formulate several problems which could complete the present results.
Adrian I. Ban, Lucian Coroianu
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Ranking Fuzzy Numbers Based on the Mean and Fuzzy Degree of Fuzzy Number
Applied Mechanics and Materials, 2012In this paper, a novel approach to ranking fuzzy numbers based on the mean and the fuzzy degree of fuzzy number is proposed. In the approach, a new ranking index that is comprehensive consideration of the mean and the fuzzy degree of fuzzy number is constructed, and then the properties of the ranking index are given.
Gui Xiang Wang, Guang Tao Zhou
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Setback in ranking fuzzy numbers: a study in fuzzy risk analysis in diabetes prediction
Artificial Intelligence Review, 2022Maryam Sotoudeh-Anvari +1 more
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