Neural Network Ensemble Based on General Entropy and Its Application

摘要：

Neural network ensemble (NNE) can remarkably heighten the generalization ability of learning systems through training multiple neural networks and combining their results.In this paper, a new neural network ensemble based on general entropy (NNEGE) and Bagging is proposed and then employed to forecast GDP of Jiangmen city with favorable results obtained,which illustrates that NNEGE is generally superior to NNE with simple average (NNESA), and valid and feasible for time series forecasting.

关键词： Neural Network Ensemble General Entropy Bagging Time Series Forecasting

作者: LIN Jian ZHU Bangzhu

作者单位: School of Management University of Wuyi Jiangmen, Guangdong 529020, China School of Management, University of Wuyi, Jiangmen, Guangdong 529020, China ;School of Economic and

会议类型: 国际会议

会议名称: 第一届国际计算机新科技与教育学术会议(Proceedings of the First International Conference on Computer Science & Education ICCSE2006)

会议地点: 厦门

会议语种:英文

页码: 807-810

在线出版日期: 2006-07-27（万方平台首次上网日期，不代表论文的发表时间）