DocumentCode
2972689
Title
Improving the back propagation learning speed with adaptive neuro-fuzzy technique
Author
Huang, Yo-Ping ; Chang, Chih Cheng ; Huang, Chi Chang
Author_Institution
Dept. of Comput. Sci. & Eng., Tatung Inst. of Technol., Taipei, Taiwan
Volume
3
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
2897
Abstract
A neuro-fuzzy technique is presented to improve the standard back propagation learning speed. By adjusting both the learning rate and accelerator parameters based on the system error and change of the error direction, the convergent rate of the proposed technique is found to be superior to that yielded by the conventional approach. Simulation results are given to demonstrate the applicability and efficiency of the proposed method.
Keywords
backpropagation; feedforward neural nets; multilayer perceptrons; pattern recognition; adaptive neuro-fuzzy technique; backpropagation learning speed; convergent rate; error direction; learning rate; Computational complexity; Computer errors; Computer science; Fuzzy neural networks; Joining processes; Neural networks; Neurons; Probes; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.714328
Filename
714328
Link To Document