DocumentCode
2591182
Title
Using genetic algorithm for extension and fitting of belief measures and plausibility measures
Author
Wang, Zhenyuan ; Wang, Jia
Author_Institution
Dept. of Syst. Sci. & Ind. Eng., State Univ. of New York, Binghamton, NY, USA
fYear
1996
fDate
19-22 Jun 1996
Firstpage
348
Lastpage
350
Abstract
Determining some special types of fuzzy measures is an important topic in systems research. It has wide applications in various areas. Some construction strategies, such as statistics from given input-output data, have been developed recently. This paper investigates another strategy of construction: extending or optimally revising a given set function to be a belief measure or a plausibility measure
Keywords
belief maintenance; fuzzy logic; fuzzy set theory; genetic algorithms; system theory; belief measures; construction strategies; fuzzy measures; genetic algorithm; input-output data; least square method; optimal revision; optimization; plausibility measures; set function extension; set function fitting; statistics; systems research; Biological cells; Computer science; Fitting; Fuzzy sets; Genetic algorithms; Genetic engineering; Industrial engineering; Least squares methods; Optimization methods; Power measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 1996. NAFIPS., 1996 Biennial Conference of the North American
Conference_Location
Berkeley, CA
Print_ISBN
0-7803-3225-3
Type
conf
DOI
10.1109/NAFIPS.1996.534757
Filename
534757
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