Optimization of BP Neural Network Classifier using Genetic Algorithm

摘要：

In this paper, a new BP neural network classifier was constructed and optimized by Genetic Algorithm, first, the BP neural network was improved by using genetic algorithm2 to train the initial weights values of the BP neural network3, second, a new classifier was constructed based on the new BP neural network optimized by Genetic Algorithm. Finally, data simulation experiment was taken and the result of data simulation with famous IRIS data shows that the new BP neural network classifier improved by the Genetic Algorithm has higher accuracy of classification and greater gradient of convergence than the BP Neural Network classifier which Proposed in literature3.

关键词： Genetic Algorithm BP neural network/ BP neural network classifier Convergence Weight

作者: Zhou Weihong Xiong Shunqing Yuan Sha

作者单位: School of Mathematics & Computer Science Yunnan Nationalities University, YNU Kunming, China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Automation Engineering(ICCAE 2011)(2011年第三届IEEE计算机与自动化工程国际会议)

会议地点: 重庆

会议语种:英文

页码: 301-304

在线出版日期: 2011-01-21（万方平台首次上网日期，不代表论文的发表时间）