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	Nonlinear Time Series Prediction Using High Precision Neural Network
	Zhou Jiehua ; Peng Xiafu ; Liu Lisang ; Peng XF(彭侠夫)
	2011
英文摘要	Conference Name:3rd International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2011). Conference Address: Shanghai, PEOPLES R CHINA. Time:JAN 06-07, 2011.; A new type of high precision back propagation (BP) neural network model was proposed and applied to nonlinear time series for improving its prediction accuracy. In order to optimize the neural network structure, it uses the correlation analysis to select the number of input node for BP neural network at first. Second, it uses grey clustering method to select the initial number of hidden node for BP neural network, then using the grey correlation analysis method to analyze the correlation degree between hidden node output and network output and according to the size of correlation degree to delete the redundant hidden nodes. Meanwhile, in order to improve model prediction accuracy, it increases the direct connection between the input layer and output layer. Finally, prediction results show that the proposed model has good prediction capability.
语种	英语
出处	http://dx.doi.org/10.4028/www.scientific.net/AMM.48-49.745
出版者	APPL MECH MATER
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/86468]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Zhou Jiehua,Peng Xiafu,Liu Lisang,et al. Nonlinear Time Series Prediction Using High Precision Neural Network. 2011-01-01.

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