基于BP算法的小波神经网络及其在洪水预报中的应用

Ping Hu
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引用次数: 4

摘要

众所周知,径流洪水预报的应用对我们来说意义非凡。本文利用强大的人工神经网络对洪水预报过程进行了详细的检测。利用BP思想对小波神经网络进行挤压,得到小波神经网络的学习算法。网络隐藏层节点的确定采用故障检测的方法。激活函数属于morlet小波函数,网络结构模型属于371。结果表明,利用该模型对1996年太阳日的洪水资料进行预测和分析,可以提供可靠的预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wavelet neural network based on BP algorithm and its application in flood forecasting
As is well known, it is the application of runoff flood forecasting that is extraordinary significant for us. A detailed detection of the flood forecasting process has been carried out using powerful artificial neural network in this paper. Learning algorithmof wavelet neural network was produced by extruding it in BP idea.The determination of network hiddenlayer nodes utilizes the medthod of tring fault. Activation function belongs to morlet wavelet function, and the modle of net structure belongs to 371. It is shown that the reliable prediction accury could be provided by using this model for predicting and analysising for the flood data of solar Da in 1996.
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