An improved similarity measure for generalized fuzzy numbers and its application to fuzzy risk analysis
| Autor: | Sanaz Nikfalazar, Hadi Akbarzadeh Khorshidi |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Fuzzy clustering Fuzzy classification Fuzzy measure theory Mathematics::General Mathematics business.industry Pattern recognition 02 engineering and technology computer.software_genre Defuzzification 020901 industrial engineering & automation Fuzzy mathematics 0202 electrical engineering electronic engineering information engineering Fuzzy set operations Fuzzy number 020201 artificial intelligence & image processing Artificial intelligence Data mining business computer Software Membership function Mathematics |
| Zdroj: | Applied Soft Computing. 52:478-486 |
| ISSN: | 1568-4946 |
| DOI: | 10.1016/j.asoc.2016.10.020 |
| Popis: | Display Omitted A new method for similarity measure of the generalized trapezoidal fuzzy numbers.Proven properties of the new proposed method.Better performance in comparison with the previous methods.Application on fuzzy risk analysis.An example of risk level classification. This paper presents an improved method to compute the degree of similarity between generalized trapezoidal fuzzy numbers. The proposed similarity measure contains many features of fuzzy numbers such as geometric distance, center of gravity (COG), area, perimeter, and height. The previous methods are criticized via presenting some examples. In addition, the performance of the proposed methods is compared by the existing similarity measures using twenty different sets of generalized trapezoidal fuzzy numbers. Furthermore, the proposed method is used for fuzzy risk analysis based on similarity measures. Finally, an example is introduced to illustrate the fuzzy risk analysis. |
| Databáze: | OpenAIRE |
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