A Novel Dynamic Weight Neural Network Ensemble Model

摘要：

　　Neural network is easy to fall into the minimum and over-fitting in the application.The paper proposes a novel dynamic weight neural network ensemble model (DW-NNE).The Bagging algorithm generates certain neural network individuals which then are selected by the k-means clustering algorithm.In addition,for the integrated output problems,the paper proposes a dynamic weight model which is based on fuzzy neural network with accordance to the ideas of dynamic weight.The experimental results show that the integrated approach can achieve better prediction accuracy compared to the traditional single model and neural network ensemble model.

关键词： Ensemble Model Neural Network Dynamic Weight K-means clustering

作者: Kewen Li Wenying Liu Kang Zhao Weishan Zhang Lu Liu

作者单位: College of Computer & Communication Engineering China University of petroleum Qingdao,Shandong Province,China

会议类型: 国际会议

会议名称: 2014International Conference on Identification,Information and Knowledge in The Internet of Things(2014信息与知识物联网国际会议)

会议地点: 北京

会议语种:英文

页码: 22-27

在线出版日期: 2014-10-17（万方平台首次上网日期，不代表论文的发表时间）