Using Modular Neural Network with Artificial Bee Colony Algorithm for Classification

摘要：

　　The Artificial bee colony (ABC) algorithm has been used in several optimization problems, including the optimization of synaptic weights from an Artificial Neural Network (ANN).However, it is easy to trap in local minimum and not enough to generate a robust ANN.Modular neural networks (MNNs) are especially efficient for certain classes of regression and classification problems, as compared to the conventional monolithic artificial neural networks.In this paper, we present a model of MNN based on ABC algorithm (ABC-MNN).The experiments show that, compared to the monolithic ABC NN model, classifier designed in this model has higher training accuracy and generalization performance.

关键词： Modular Neural Network Artificial Bee Colony Algorithm Learning Algorithm

作者: Wei-Xin Ling Yun-Xia Wang

作者单位: School of Science, South China University of Technology, Guangzhou, China

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 396-403

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）