Analysis of an impact linear relationship between input variables having on prediction of BP neural network

doi:10.1109/AIMSEC.2011.6009833

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	Analysis of an impact linear relationship between input variables having on prediction of BP neural network
	Li, Zhendong 1; Sun, Wei 2
	2011
会议录名称	2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Proceedings
页码	5412-5416
出版者	IEEE Computer Society
摘要	Since the artificial neural networks were put forward, they have been used widely in predicting, and achieved good effect. But few pay attention to what an effect input variables with the linear correlation will have on the artificial neural network. Based on one example, I analyzed and studied an influence which the input variables with linear relation have on stability and prediction effect of BP neural networks predictive model. The results show that when the linear correlation between input variables is eliminated linear correlation, prediction accuracy and stability of BP neural networks can be improved. © 2011 IEEE.
关键词	Forecasting BP neural networks Input variables Linear correlation Linear relation Linear relationships Prediction accuracy Predictive modeling Principal Components
DOI	10.1109/AIMSEC.2011.6009833
收录类别	EI
语种	英语
EI入藏号	20114014386854
文献类型	会议论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/9825
专题	兰州财经大学
作者单位	1.School of Information Engineering, Lanzhou University of Finance and Economics, Lanzhou, China; 2.School of Statistics, Lanzhou University of Finance and Economics, Lanzhou, China
推荐引用方式 GB/T 7714	Li, Zhendong,Sun, Wei. Analysis of an impact linear relationship between input variables having on prediction of BP neural network[C]:IEEE Computer Society,2011:5412-5416.