小波神经网络日长预报算法研究  

RESEARCH ON ALGORITH OF WAVELET NEURAL NETWORK FOR FORECASTING LENGTH OF DAY

作　　者：王宇谱[1] 吕志平[1] 

机构地区：[1]解放军信息工程大学测绘学院,郑州450052

出　　处：《大地测量与地球动力学》2012年第1期127-131,共5页Journal of Geodesy and Geodynamics

基　　金：国家自然科学基金(40874008)

摘　　要：针对BP神经网络的不足,利用小波基函数替代BP神经网络激活函数,对BP神经网络的权值及阈值进行优化,得到优化后的小波神经网络,有效地避免了局部极值的影响,且收敛速度快。将此应用于日长预报,取得了良好的预报效果。Artificial neural networks （BP network, i.e. Back-Propagation network） can be used to forecast the Length of Day （LOD） for its advantage of parallel disposal data and strong non-linear 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.

关 键 词：日长预报 小波神经网络 BP神经网络 去噪 小波基函数 

分 类 号：P207[天文地球—测绘科学与技术]