Improved BP Neural Network Algorithm through Genetic Algorithm Optimization and Its Simulation

被引：0

作者：

Jiang, Junsheng ^{[1
]}

机构：

[1] Weifang Univ, Sch Mech & Elect Engn, Weifang, Shandong, Peoples R China

来源：

2011 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION AND INDUSTRIAL APPLICATION (ICIA2011), VOL IV | 2011年

关键词：

BP neural network; genetic algorithm; optimization;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Aiming at the drawbacks of slowly converging and easily getting in the local minimum appearing in the BP neural network, this paper combines the general optimization of the genetic algorithm together with the local optimization of BP neural network to improve the performance of BP neural network. The numerical experiment shows that, compared with the original BP neural network, the improved BP neural network can effectively reduce the average error of model calculation and prediction, greatly cut the times of iteration, and raise the calculation accuracy and convergence speed. This paper also demonstrates the ability of the genetic algorithm to improve the performance of BP neural network.

引用

页码：330 / 332

页数：3