DocumentCode
288370
Title
An automated approach for selecting the learning rate and momentum in backpropagation networks
Author
Zaghw, A. ; Dong, W.M.
Author_Institution
Dept. of Structural Eng., Cairo Univ., Giza, Egypt
Volume
1
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
464
Abstract
This paper describes how the backpropagation neural network (BP) can be modified to employ the conjugate gradient method (CG) for speeding up the training process. The application of the conjugate gradient method in this paper was achieved by the appropriate selection of each of the learning rate and momentum in a regular backpropagation program
Keywords
backpropagation; conjugate gradient methods; neural nets; backpropagation networks; conjugate gradient method; learning rate; momentum; training process; Backpropagation; Character generation; Civil engineering; Equations; Gradient methods; Intelligent networks; Neural networks; Structural engineering; Supervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374207
Filename
374207
Link To Document