Title :
A fuzzy method for automatic generation of membership function using fuzzy relations from training examples
Author :
Cano, Janette C. ; Nava, Patricia A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas Univ., El Paso, TX, USA
Abstract :
Fuzzy systems rely on membership functions to represent input values for problem presentation and eventual problem solution. These can be generated in different ways, one of which is obtaining an expert to define the functions. This method is not always cost effective or available, so automatic membership function definition is extremely desirable Many methods for constructing membership functions based on knowledge engineering have been developed. Previous work has shown that statistical methods can be used to generate these membership functions. The quality of the result, however, is very application dependent. This study focuses on a method of automatic membership function generation that relies on the use of fuzzy relations. This paper describes the implementation of one such method, and examines its application to several data sets, including the identification of vowel sounds in spoken English.
Keywords :
computational linguistics; expert systems; fuzzy logic; fuzzy set theory; fuzzy systems; knowledge acquisition; learning by example; automatic membership function generation; data sets; fuzzy relations; fuzzy systems; input values; knowledge engineering; problem presentation; problem solution; spoken English; statistical methods; training examples; vowel sound identification; Consumer products; Costs; Expert systems; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Knowledge acquisition; Knowledge engineering; Mathematical model; Uncertainty;
Conference_Titel :
Fuzzy Information Processing Society, 2002. Proceedings. NAFIPS. 2002 Annual Meeting of the North American
Print_ISBN :
0-7803-7461-4
DOI :
10.1109/NAFIPS.2002.1018047