نتایج جستجو برای: fuzzy ranking technique

تعداد نتایج: 723546  

Multi attribute decision making methods are considered as one of the most useful methods for solving ranking problems. In some decision making problems, while the alternatives for corresponding criteria are compared in a pairwise comparison manner, if the criteria are inherently fuzzy, debates will arise in ranking alternatives due to the closeness of the values of the criteria. In this researc...

Journal: :Risk Governance and Control: Financial Markets and Institutions 2017

H. Zhang J. Ge J. Xie Y. Song Z. Zhang

A novel ranking method based on multi-time information fusion is proposed for intuitionistic fuzzy sets (IFSs) and applied to the threat assessment problem, a multi-attribute decision making (MADM) one. This method integrates a designed intuitionistic fuzzy entropy (IFE), the closeness degree of technique for order preference by similarity to ideal solution (TOPSIS), the decision maker¡¯s (DM¡¯...

Journal: :علوم 0

in this paper, by using a new approach on distance between two fuzzy numbers, we construct a new ranking system for fuzzy number which is very realistic and also matching our intuition as the crisp ranking system on r.

Journal: :Inf. Sci. 2016
Kok Chin Chai Kai Meng Tay Chee Peng Lim

In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets and the Dempster–Shafer Theory (DST) of evidence, is devised. The use of fuzzy targets to reflect human viewpoints in fuzzy ranking is not new. However, different fuzzy targets can lead to contradictory fuzzy ranking results; making it difficult to reach a final decision. In this paper, the result...

2004
Jee-Hyong Lee Hyung Lee-Kwang

Ranking fuzzy numbers is one of very important research topics in fuzzy set theory because it is a base of decision-making in all application areas. However, fuzzy numbers cannot be easily arranged in the order of magnitude because they represent uncertain and vague values. When two fuzzy numbers overlap with each other, a fuzzy number may not be considered absolutely larger than the other. Tha...

Journal: :international journal of industrial mathematics 0
rahim saneifard department of applied mathematics‎, ‎urmia branch‎, ‎islamic azad university‎, ‎urmia‎, ‎iran.‎‎ rasoul saneifard department of engineering technology‎, ‎texas southern university‎, ‎houston‎, ‎texas‎, ‎usa.

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 signal/noise ratios, where the signal and the noise are defined as the middle-point and the spread of each $gamma$-cut of a fuzzy number, respectively. we use the va...

2012
Pushpinder Singh

Ranking of fuzzy sets plays an important role in decision making, optimization, forecasting, etc. Fuzzy sets must be ranked before an action is taken by a decision maker. Fuzzy sets with different heights are a generalization of the ordinary fuzzy sets. In this paper, with the help of several counterexamples, it is proved that the ranking method proposed by Lee and Chen (Expert Systems with App...

Journal: :Soft Comput. 2011
Amit Kumar Pushpinder Singh Parmpreet Kaur Amarpreet Kaur

Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. In this paper, with the help of several counter examples it is proved that ranking method proposed by Chen and Chen (Expert Syst Appl 36:6833–6842, 2009) is incorrect. The main aim of this paper is to propose a new approac...

2015
Preetibala Deshmukh Vikram Garg G. Shrivastava K. Sharma V. Kumar Monika Yadav Pradeep Mittal Rashmi Sharma Kamaljit Kaur

A survey of various link analysis and clustering algorithms such as Page Rank, Hyperlink-Induced Topic Search, Weighted Page Rank based on Visit of Links K-Means, Fuzzy K-Means. Ranking algorithms illustrated, Weighted Page Rank is more efficient than Hyperlink-induced Topic Search Whereas clustering algorithms has described Fuzzy Soft, Rough K-Means is a mixture of Rough K-Means and fuzzy soft...

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