Study of the Optimized Algorithms of BP Neural Network
YANG Li-fen, CAI Zhi-hua (School of Computer Science, China University of Geosciences, Wuhan 430074, China)
To solve the BP neural network's disadvantages of trapping to a local optimum and being prone to converge to minimum,the authors propose two new improved algorithms based on BP neural network based on the characteristic of Genetic Algorithm and Gene Expression Programming respectively. One is GA-BP algorithm in which the weights and thresholds of BP neural network were optimized with GA; the other is GEP-BP which uses GEP to modify BP neural network ,including the architecture ,the weights and thresholds. Finally,the two new algorithms were implemented,and standard data was used to test them. Compared to BP neural network, the results show that these two new algorithms are effective and feasible method in real application.
【CateGory Index】： TP183