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小波神经网络日长预报算法研究
  • 期刊名称:大地测量学与地球动力学
  • 时间:0
  • 页码:759-774
  • 语言:中文
  • 分类:P207[天文地球—测绘科学与技术]
  • 作者机构:[1]解放军信息工程大学测绘学院,郑州450052
  • 相关基金:国家自然科学基金(40874008)
  • 相关项目:动态参考框架网格计算模型与方法研究
中文摘要:

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。

英文摘要:

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.

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