DocumentCode
2272978
Title
A fuzzy neural network with trapezoid fuzzy weights
Author
Ishibuchi, Hisao ; Morioka, Kouichi ; Tanaka, Hideo
Author_Institution
Dept. of Ind. Eng., Osaka Prefectural Univ., Osaka, Japan
fYear
1994
fDate
26-29 Jun 1994
Firstpage
228
Abstract
Proposes a fuzzy neural network architecture whose weights are given as trapezoid fuzzy numbers. The proposed fuzzy neural network can handle fuzzy inputs as well as real inputs. In both cases, outputs from the fuzzy neural network are fuzzy numbers. Next, we derive a learning algorithm from a cost function defined for level sets (i.e. α-cuts) of fuzzy outputs and fuzzy targets. Lastly, we examine the ability of the proposed fuzzy neural network to implement fuzzy IF-THEN rules by computer simulation
Keywords
fuzzy neural nets; learning (artificial intelligence); neural net architecture; virtual machines; α-cuts; computer simulation; cost function; fuzzy IF-THEN rules; fuzzy inputs; fuzzy neural network architecture; fuzzy numbers; fuzzy outputs; fuzzy targets; learning algorithm; level sets; real inputs; trapezoid fuzzy weights; Computer architecture; Computer simulation; Cost function; Fuzzy neural networks; Fuzzy sets; Industrial engineering; Level set; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1896-X
Type
conf
DOI
10.1109/FUZZY.1994.343681
Filename
343681
Link To Document