DocumentCode
3122257
Title
The improvement of a fuzzy neural network based on backpropagation
Author
Hua, Qung ; Ha, Ming-Hu
Author_Institution
Machine Learning Centre, HeBei Univ., Baoding, China
Volume
4
fYear
2002
fDate
4-5 Nov. 2002
Firstpage
2237
Abstract
Some discussions on the fuzzy neural network architecture and algorithm have been put forward, whose weights are given as special fuzzy numbers, such as triangular fuzzy numbers. In this paper, we introduce the conception of strong L-R type fuzzy number, and derive a learning algorithm based on BP algorithm via level sets of strong L-R type fuzzy numbers. The special fuzzy number is weakened to the common case. Then the range of application is enlarged. Finally, the initial experiment in fuzzy classification is shown.
Keywords
backpropagation; fuzzy neural nets; fuzzy set theory; neural net architecture; pattern classification; backpropagation; fuzzy classification; fuzzy neural network; fuzzy numbers; fuzzy set theory; learning algorithm; Arithmetic; Cost function; Cybernetics; Electronic mail; Fuzzy neural networks; Fuzzy sets; Level set; Machine learning; Neural networks; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN
0-7803-7508-4
Type
conf
DOI
10.1109/ICMLC.2002.1175437
Filename
1175437
Link To Document