DocumentCode :
3451303
Title :
A neural expert system using fuzzy teaching input
Author :
Hayashi, Yoichi
Author_Institution :
Dept. of Comput. & Inf. Sci., Ibaraki Univ., Japan
fYear :
1992
fDate :
8-12 Mar 1992
Firstpage :
485
Lastpage :
491
Abstract :
The author previously (1990, 1991) proposed a fuzzy neural expert system and provided a method to extract automatically fuzzy IF-THEN rules from a trained neural network. The previous work is extended and a neural expert system is proposed using fuzzy teaching input. The neural expert system can perform generalization of the information derived from training data with fuzzy teaching input and embodiment of knowledge in the form of a fuzzy neural network, where the fuzzy teaching input is subjectively given by domain experts: and extraction of fuzzy IF-THEN rules with linguistic relative importance of each proposition in an antecedent (IF-part) from a trained neural network. A method is proposed to extract automatically fuzzy IF-THEN rules from the trained neural network generated by training data with fuzzy teaching input
Keywords :
expert systems; fuzzy logic; knowledge acquisition; neural nets; FNES; fuzzy IF-THEN rules; fuzzy neural expert system; fuzzy teaching input; information generalization; linguistic relative importance; rule extraction; Biological neural networks; Data mining; Education; Expert systems; Fuzzy neural networks; Fuzzy systems; Hybrid intelligent systems; Neural networks; Pediatrics; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1992., IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0236-2
Type :
conf
DOI :
10.1109/FUZZY.1992.258661
Filename :
258661
Link To Document :
بازگشت