计算机工程与应用2018，Vol.54Issue(10)：158-163,6.DOI:10.3778/j.issn.1002-8331.1612-0379
改进人工蜂群优化BP神经网络的分类研究
Study on classification of improved artificial bee colony algorithm to optimi-zation of BP neural network
摘要
Abstract
Due to the issues of BP neural network, which is sensitive to initial weights and easy to make the objective function into local optimum,and the disadvantages of weak local search ability and poor exploitation in standard artificial bee colony algorithm,a training method of neural network called improved artificial bee colony and back propagation is proposed.First,modify artificial bee colony algorithm inspired by the thought of differential evolution and make a more accurate description of searching behavior of onlooker bees.Second,avoid BP neural network falling into local optimum, using improved artificial bee colony to globally search the initial weights of BP neural network.Last,the datasets are tested by the new algorithm.The experiment shows compared with traditional BP neural network,the algorithm has higher clas-sification correctness and better generalization.关键词
BP神经网络/分类/泛化能力/人工蜂群Key words
BP neural network/classification/generalization/artificial bee colony分类
信息技术与安全科学引用本文复制引用
韦鹏宇,潘福成,李帅..改进人工蜂群优化BP神经网络的分类研究[J].计算机工程与应用,2018,54(10):158-163,6.基金项目
辽宁省科学技术计划项目(No.2015106015). （No.2015106015）
