A note on ranking generalized fuzzy numbers

被引：28

作者：

Xu, Peida ^{[2
,3
,6
]}

Su, Xiaoyan ^{[2
,4
]}

Wu, Jiyi ^{[6
]}

Sun, Xiaohong ^{[3
]}

Zhang, Yajuan ^{[1
,5
]}

Deng, Yong ^{[1
]}

机构：

[1] Southwest Univ, Coll Comp & Informat Sci, Chongqing 400715, Peoples R China

[2] Shanghai Jiao Tong Univ, Sch Elect & Informat Technol, Shanghai 200030, Peoples R China

[3] Shanghai Ocean Univ, Coll Food Sci & Technol, Shanghai, Peoples R China

[4] Xiangtan Univ, Key Lab Intelligent Comp & Informat Proc, Minist Educ, Xiangtan, Hunan, Peoples R China

[5] SW Univ Sci & Technol, Key Subject Lab Natl Def Radioact Waste & Environ, Mianyang, Peoples R China

[6] Hangzhou Normal Univ, Hangzhou Key Lab E Bussiness & Informat Secur, Hangzhou, Zhejiang, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2012年 / 39卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Generalized fuzzy numbers; Ranking fuzzy numbers; Modification;

D O I：

10.1016/j.eswa.2011.12.062

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Ranking fuzzy numbers plays an important role in decision making under uncertain environment. Recently, Chen and Sanguansat (2011) [Chen, S. M. & Sanguansat, K. (2011). Analyzing fuzzy risk based on a new fuzzy ranking method between generalized fuzzy numbers. Expert Systems with Applications, 38(3), (pp. 2163-2171)] proposed a method for ranking generalized fuzzy numbers. It considers the areas on the positive side, the areas on the negative side and the heights of the generalized fuzzy numbers to evaluate ranking scores of the generalized fuzzy numbers. Chen and Sanguansat's method (2011) can overcome the drawbacks of some existing methods for ranking generalized fuzzy numbers. However. in the situation when the score is zero, the results of the Chen and Sanguansat's ranking method (2011) ranking method are unreasonable. The aim of this short note is to give a modification on Chen and Sanguansat's method (2011) to make the method more reasonable. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：6454 / 6457

页数：4

共 7 条

[1]

[Anonymous], 2006, COMPUT MATH APPL, DOI DOI 10.1016/j.camwa.2004.11.022

[2] Analyzing fuzzy risk based on a new fuzzy ranking method between generalized fuzzy numbers [J].

Chen, Shyi-Ming ;

Sanguansat, Kata .

EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (03) :2163-2171

[3] Fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads [J].

Chen, Shyi-Ming ;

Chen, Jim-Ho .

EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (03) :6833-6842

[4] A new approach for ranking fuzzy numbers by distance method [J].

Cheng, CH .

FUZZY SETS AND SYSTEMS, 1998, 95 (03) :307-317

[5] Ranking fuzzy numbers with an area between the centroid point and original point [J].

Chu, TC ;

Tsao, CT .

COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2002, 43 (1-2) :111-117

[6]

Yager R.R., 1978, PROC 978 CDC, P1435

[7] A TOPSIS-based centroid-index ranking method of fuzzy numbers and its application in decision-making [J].

Yong, D ;

Qi, L .

CYBERNETICS AND SYSTEMS, 2005, 36 (06) :581-595

← 1 →