RESEARCH ON ALGORITH OF WAVELET NEURAL NETWORK FOR FORECASTING LENGTH OF DAY
Wang Yupu ;and Lü Zhiping
Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450052
Abstract Artificial neural networks (BP network, i.e. BackPropagation network) can be used to forecast the Length of Day (LOD) for its advantage of parallel disposal data and strong nonlinear mapping ability, but it can be easily affected by local minimum and resulting in slow convergence speed. Aiming at the shortage of the BP neural network, the wavelet basis function is used instead of the activation function of the BP neural network to improve its weight and threshold, then come into being optimized wavelet neural network which could effectually avoid local minimum and has swift convergence speed. As it is used to forecast LOD, good effects have been achieved.
Key words ：
LOD(Length of Day) forecast
wavelet neural network
BP neural network
denoising
wavelet basis function
Received: 01 January 1900
Corresponding Authors:
Wang Yupu
Cite this article:
Wang Yupu,and Lü Zhiping. RESEARCH ON ALGORITH OF WAVELET NEURAL NETWORK FOR FORECASTING LENGTH OF DAY[J]. , 2012, 32(1): 127-131.
Wang Yupu,and Lü Zhiping. RESEARCH ON ALGORITH OF WAVELET NEURAL NETWORK FOR FORECASTING LENGTH OF DAY[J]. jgg, 2012, 32(1): 127-131.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2012/V32/I1/127
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