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
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;
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
DOI :
10.1109/NAFIPS.1996.534757
