作　　者： ; ;

机构地区： 湖南大学土木工程学院

出　　处： 《湖南大学学报（自然科学版）》 2007年第6期15-18,共4页

摘　　要： 利用小波网络构造模型的优化组合函数,建立了城市用水量非线性组合预测模型.将非线性组合函数的拟合转化为小波网络参数的估计,采用遗忘因子法训练网络的权值,利用递推预报误差算法训练尺度因子和平移因子.实例表明,该方法具有很强的泛化能力与自适应数据和函数变化的能力,能够有效提高预测精度,克服了线性组合预测方法适应性不强的问题. In order to overcome the drawbacks in linear combination forecasting modeling, the wavelet network method was applied to establish the optimal combination function for developing the nonlinear combination forecasting modeling of urban water consumption. By this method, the fitting of the nonlinear combination function was transformed into parameters estimation of wavelet network. The forgetting factor method was used to train the weights of wavelet network and scale factors, and displacement factors were trained by the predicting error method. The numerical example shows that the proposed combination model is feasible and effective in promoting the accuracy of forecasting.

关 键 词： 算法 城市用水量 非线性组合预测 小波网络

领　　域： [水利工程]