Analyzing fuzzy risk based on a new similarity measure between interval-valued fuzzy numbers

In this paper, we present a new similarity measure between interval-valued fuzzy numbers. It combines the concepts of geometric distance, the perimeters and the spreads of differences between interval-valued fuzzy numbers on both the X-axis and the Y-axis. The proposed method can overcome the drawba...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 5; pp. 2869 - 2874
Main Authors Sanguansat, K., Shyi-Ming Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Arithmetic
Computer science
Cybernetics
Fuzzy risk analysis
Fuzzy sets
Gold
Information analysis
Interval-valued fuzzy numbers
Linguistic terms
Linguistic values
Machine learning
Risk analysis
Similarity measures
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Summary:In this paper, we present a new similarity measure between interval-valued fuzzy numbers. It combines the concepts of geometric distance, the perimeters and the spreads of differences between interval-valued fuzzy numbers on both the X-axis and the Y-axis. The proposed method can overcome the drawbacks of the existing similarity measures. Finally, based on the proposed similarity measure between interval-valued fuzzy numbers, we present a new fuzzy risk analysis algorithm for dealing with fuzzy risk analysis problems. The proposed method provides us with a useful way for handling the fuzzy risk analysis problems.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212584