On rule checking and learning in an acupuncture diagnosis fuzzy expert system by genetic algorithm

Author

Zhang, Lei ; Wang, Lisong ; Zang, Yuwen ; Seki, Hirohisa ; Itoh, Hidenori

Author_Institution

Dept. of Intelligence & Comput. Sci., Nagoya Inst. of Technol., Japan

Volume

2

fYear

1995

fDate

20-24 Mar 1995

Firstpage

455

Abstract

ADFL is an acupuncture diagnosis expert system based on fuzzy logic, which has been reported by Zhang et al. (1993, 1994). This paper gives a method to learn ADFL rules by genetic algorithms (GAs), and a technique to optimize and check fuzzy membership functions. For any length gene, we present an extended ordinal representation method. A fitness function described with fuzzy rules is explained. The experimental result indicates this method is effective

Keywords

fuzzy logic; genetic algorithms; knowledge based systems; medical diagnostic computing; medical expert systems; acupuncture diagnosis fuzzy expert system; fitness function; fuzzy logic; fuzzy membership functions; fuzzy rules; genetic algorithm; rule checking; rule learning; Computer science; Diagnostic expert systems; Expert systems; Fuzzy logic; Fuzzy reasoning; Fuzzy sets; Genetic algorithms; Humans; Hybrid intelligent systems; Medical treatment;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int

Conference_Location

Yokohama

Print_ISBN

0-7803-2461-7

Type

conf

DOI

10.1109/FUZZY.1995.409726

Filename

409726