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Radial basis function network for prediction of hydrological time series

机译:径向基函数网络预测水文时间序列

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In this study, a network using radial basis functions as the mapping function in the evolutionary equation for prediction of time series is presented. A radial basis function network requires the determination of the number of centres of the radial basis functions, their receptive field widths, and the linear weights of the network output layer. Methods to estimate the widths of the receptive fields, and the number of centres for the radial basis functions are introduced in the study. The latter is based on the concept of the Generalized Degrees of Freedom. The linear weights are determined by the least squares method. The predictions by the proposed method when compared with the actual values of four hydrometeorological data sets, are better than those by the traditional approach of fixing the number of centres.
机译:在这项研究中,提出了使用径向基函数作为演化方程中的映射函数来预测时间序列的网络。径向基函数网络需要确定径向基函数的中心数,它们的接收场宽度以及网络输出层的线性权重。在研究中介绍了估计感受野宽度的方法以及径向基函数的中心数。后者基于广义自由度的概念。线性权重通过最小二乘法确定。与四个水文气象数据集的实际值相比,所提方法的预测要好于固定中心数量的传统方法的预测。

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