Research on Monthly Rainfall Forecast Model Based on RBF Neural Network
Research on Monthly Rainfall Forecast Model Based on RBF Neural Network
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基于RBF神经网络的月降雨量预报模型研究
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
J. Gan
中科院分区：
文献类型：
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作者：
J. Gan
针对月降雨量非线性较强的特点，以合肥地区1990 ~ 2010年月降雨量数据为时间序列，利用RBF神经网络，建立了一种基于RBF神经网络的月降雨量预报模型。首先介绍了RBF神经网络的结构，讨论了RBF神经网络在月降雨量预测中的应用。然后，利用MATLAB工具箱的功能，建立了月降雨量的网络模型。最后，通过仿真实验和研究，比较了RBF神经网络与传统BP网络的预测结果。仿真结果表明，RBF神经网络模型优于传统的BP神经网络。
Owing to the strong nonlinearity of monthly rainfall,taking 1990 ~ 2010 monthly rainfall data in the Hefei area as the time series and using the RBF neural network,a new monthly forecast model is developed based on RBF neural network. Firstly,introduce the structure of RBF neural networks and discuss the RBF neural networks application for predicting the monthly rainfall. And then,the functions of MATLAB toolbox are adopted to create a network model for the monthly rainfall. Finally,RBF neural network and traditional BP network are compared in their prediction results each other through simulation experiments and studies. Simulation results show that the RBF neural network model is superior to traditional BP neural network.