Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights

Authors:
Shyi-Ming Chen;Abdul Munif;Guey-Shya Chen;Hsiang-Chuan Liu;Bor-Chen Kuo
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC and Graduate Institute of Educational Measurement and Statisti ...;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;Graduate Institute of Educational Measurement and Statistics, National Taichung University of Education, Taichung, Taiwan, ROC;Department of Biomedical Informatics, Asia University, Taichung, Taiwan, ROC;Graduate Institute of Educational Measurement and Statistics, National Taichung University of Education, Taichung, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 8
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Abstract

In this paper, we present a new method for fuzzy risk analysis based on the proposed new fuzzy ranking method for ranking generalized fuzzy numbers with different left heights and right heights. First, we present a fuzzy ranking method for ranking generalized fuzzy numbers with different left heights and right heights. The proposed method considers the areas of the positive side, the areas of the negative side and the centroid values of generalized fuzzy numbers as the factors for calculating the ranking scores of generalized fuzzy numbers with different left heights and right heights. It can overcome the drawbacks of the existing fuzzy ranking methods. Then, we propose a new method for fuzzy risk analysis based on the proposed fuzzy ranking method, where the evaluating values are represented by generalized fuzzy numbers. The proposed fuzzy risk analysis method provides us with a useful way for fuzzy risk analysis based on generalized fuzzy numbers with different left heights and right heights.