A new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights

2011 ◽  
Author(s):  
Shyi-Ming Chen ◽  
Abdul Munif ◽  
Guey-Shya Chen ◽  
Bor-Chen Kuo ◽  
Hsiang-Chuan Liu
Keyword(s):  
Risk Analysis ◽  
Fuzzy Numbers ◽  
New Method ◽  
Fuzzy Risk Analysis ◽  
Generalized Fuzzy Numbers

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

2012 ◽  
Vol 39 (7) ◽  
pp. 6320-6334 ◽  
Author(s):  
Shyi-Ming Chen ◽  
Abdul Munif ◽  
Guey-Shya Chen ◽  
Hsiang-Chuan Liu ◽  
Bor-Chen Kuo
Keyword(s):  
Risk Analysis ◽  
Fuzzy Numbers ◽  
Fuzzy Risk Analysis ◽  
Generalized Fuzzy Numbers

scholarly journals Evaluating the Efficiency of School Preceptors by Fuzzy Risk Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Rasoul Saneifard ◽  
Rahim Saneifard
Keyword(s):  
Risk Analysis ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
New Method ◽  
Arithmetic Operations ◽  
Fuzzy Risk Analysis ◽  
Fuzzy Weights

This paper presents a new method for evaluating the efficiency of school preceptors based on fuzzy number arithmetic operations. It uses fuzzy numbers to represent fuzzy grades. The fuzzy weights of criteria are automatically generated from the opinions of evaluators. The simplified fuzzy number arithmetic operations are used for calculating the average of fuzzy numbers. It can evaluate the efficiency of school preceptors in a more flexible and more intelligent manner.

A New Fuzzy Risk Analysis Method based on Generalized Fuzzy Numbers

2011 ◽  
Vol 6 (9) ◽  
Author(s):  
Xiaoyan Su ◽  
Wen Jiang ◽  
Jianling Xu ◽  
Peida Xu ◽  
Yong Deng
Keyword(s):  
Risk Analysis ◽  
Fuzzy Numbers ◽  
Analysis Method ◽  
Fuzzy Risk Analysis ◽  
Generalized Fuzzy Numbers

scholarly journals Fuzzy Risk Analysis for a Production System Based on the Nagel Point of a Triangle

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Handan Akyar
Keyword(s):  
Risk Analysis ◽  
Fuzzy Numbers ◽  
New Method ◽  
Economic Systems ◽  
Triangular Fuzzy Numbers ◽  
Ranking Methods ◽  
Analysis Problem ◽  
Centroid Point ◽  
Fuzzy Risk Analysis ◽  
Fuzzy Ranking

Ordering and ranking fuzzy numbers and their comparisons play a significant role in decision-making problems such as social and economic systems, forecasting, optimization, and risk analysis problems. In this paper, a new method for ordering triangular fuzzy numbers using the Nagel point of a triangle is presented. With the aid of the proposed method, reasonable properties of ordering fuzzy numbers are verified. Certain comparative examples are given to illustrate the advantages of the new method. Many papers have been devoted to studies on fuzzy ranking methods, but some of these studies have certain shortcomings. The proposed method overcomes the drawbacks of the existing methods in the literature. The suggested method can order triangular fuzzy numbers as well as crisp numbers and fuzzy numbers with the same centroid point. An application to the fuzzy risk analysis problem is given, based on the suggested ordering approach.

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