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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1175437
