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Research on complex financial decision making driven by geometric aggregation and intelligent optimization of high-dimensional expert information. [PDF]
Sci RepQian Y +5 more
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A linguistic hesitant fuzzy group decision-making method for sustainable human-robot collaboration. [PDF]
PLoS OneZhang X, Yang Y, Chen Q, Wang J.
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Ranking fuzzy numbers with integral value
Fuzzy Sets and Systems, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tian-Shy Liou, Mao-Jiun J. Wang
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Fuzzy Rank Acceptability Analysis: A Confidence Measure of Ranking Fuzzy Numbers
IEEE Transactions on Fuzzy Systems, 2018Ordering fuzzy quantities is a challenging problem in fuzzy sets theory that has attracted the interest of many researchers. Despite the multiple indices introduced for this purpose and due to the fact that fuzzy quantities do not have a natural order ...
B. Yatsalo, Luis Martínez
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RANKING FUZZY NUMBERS USING α-WEIGHTED VALUATIONS
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2000We studied here on some simple examples the interaction between valuation family, parameters and ranking result. The ranking method studied is 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. The valuation method considered was introduced initially by the
Detyniecki, Marcin, Yager, Ronald R.
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Ranking of fuzzy numbers by fuzzy mapping
International Journal of Computer Mathematics, 2011In this work, the concepts of interval function, the mean value and α lower percentile of a fuzzy number are presented. Also, we defined a large family of fuzzy numbers. Then, we obtained a method to rank them. Herein, the approach proposed is relatively simple in terms of computational efforts and is efficient for ranking fuzzy numbers.
B. Asady, M. Akbari, M. A. Keramati
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Ranking of Independent and Dependent Fuzzy Numbers and Intransitivity in Fuzzy MCDA
IEEE transactions on fuzzy systems, 2021Ranking of fuzzy numbers (FNs) is a key stage within fuzzy multicriteria decision analysis (FMCDA). However, the influence of FNs dependence on their ranking, including ranking alternatives within FMCDA, has not been studied yet.
B. Yatsalo +4 more
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Ranking of intuitionistic fuzzy numbers
2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), 2008The notion of fuzzy subsets was introduced by L.A.Zadeh (1965) and it was generalised to intuitionistic fuzzy subsets by K.Atanassov [1]. After the invention of intuitionistic fuzzy subsets, many real life problems are studied accurately [7, 13, 14]. The measure of fuzziness was studied in [12, 16].
V.Lakshmana Gomathi Nayagam +2 more
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RANKING-INTUITIONISTIC FUZZY NUMBERS
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2004Intuitionistic fuzzy sets are a generalization of ordinary fuzzy sets which are characterized by a membership function and a non-membership function. In this paper we consider the problem of ranking a set of intuitionistic fuzzy numbers. We adopt a statistical viewpoint and interpret each intuitionistic fuzzy number as an ensemble of ordinary fuzzy ...
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Ranking Triangular Fuzzy Numbers Using Fuzzy Set Inclusion Index
2013In this paper, an original ranking operator is introduced for Triangular Fuzzy Numbers. The purpose is to elaborate fast and efficient algorithms dealing with complicated operations and big data in fuzzy decision-making. The proposed ranking operator takes advantage of the topological relationship of two triangles, besides the Inclusion Index concept —
Boulmakoul, Azedine +3 more
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