نتایج جستجو برای: fuzzy ranking

تعداد نتایج: 122090  

Journal: :international journal of industrial mathematics 0
f. abbasi‎ department of mathematics, ayatollah amoli branch, islamic azad university, amol, ‎iran. t. allahviranloo department of mathematics, science and research branch, islamic azad university, tehran, ‎iran. s. abbasbandy department of mathematics, science and research branch, islamic azad university, tehran, ‎iran.

‎ranking fuzzy numbers is generalization of the concepts of order, and class, and so have fundamental applications. moreover, deriving the final efficiency and powerful ranking are helpful to decision makers when solving fuzzy problems. selecting a good ranking method can apply to choosing a desired criterion in a fuzzy environment. there are numerous methods proposed for the ranking of fuzzy n...

Journal: :Expert Syst. Appl. 2009
Shyi-Ming Chen Jim-Ho Chen

In this paper, we present a new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads. First, we present a new method for ranking generalized fuzzy numbers. The proposed method considers the defuzzified values, the heights and the spreads for ranking generalized fuzzy numbers. Based on the proposed method for ranking generalized f...

This paper suggests  a novel approach for ranking the most applicable fuzzy numbers, i.e.  $LR$-fuzzy numbers. Applying the  $alpha$-optimistic values of a fuzzy number, a preference criterion is proposed for ranking fuzzy numbers using the Credibility index. The main properties of the proposed  preference criterion  are also studied.  Moreover, the proposed method is   applied for ranking fuzz...

Journal: :Computers & Mathematics with Applications 1999

Ranking fuzzy numbers plays a main role in many applied models inreal world and in particular decision-making procedures. In manyproposed methods by other researchers may exist some shortcoming.The most commonly used approaches for ranking fuzzy numbers isbased on defuzzification method. Many ranking fuzzy numberscannot discriminate between two symmetric fuzzy numbers withidentical core. In 200...

2006
Shyi-Ming Chen Jim-Ho Chen

In this paper, we present a new method for ranking generalized fuzzy numbers for dealing with fuzzy risk analysis problems. The proposed method considers the defuzzified values, the heights and the spreads of generalized fuzzy numbers, simultaneously, for ranking generalized fuzzy numbers. It gets better ranking results to rank generalized fuzzy numbers than the existing methods. We also apply ...

2016
P. Malini M. Ananthanarayanan

Ranking fuzzy numbers play a vital role in decision making problems, data analysis and socio economics systems. Ranking fuzzy numbers is a necessary step in many mathematical models. Many of the methods proposed so far are non-discriminating. This paper presents a new ranking method and using which we convert the fuzzy transportation problem to a crisp valuedtransportation problem which then ca...

Journal: :Expert Syst. Appl. 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. Cheng (Cheng, C. H. (1998). A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets and Systems, 95, 307–317) pointed out that the proof of the statement ‘‘Ranking of generalized fuzzy numbers does not depe...

Journal: :international journal of industrial mathematics 0
r. saneifard department of mathematics, urmia branch, islamic azad university, urmia, iran.

the importance as well as the diculty 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 de ned as the middle-point and the spread of each a-cut of a fuzzy number, respectively. we use the value of a ...

2010
Amit Kumar Pushpinder Singh Parampreet 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 Systems with Applications 36 (2009) 6833-6842) is incorrect. The main aim of this paper is to prop...

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