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Radial basis function network for prediction of hydrological time series

机译:用于预测水文时间序列的径向基函数网络

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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:在本研究中,呈现了使用径向基础函数作为用于预测时间序列预测的映射函数的网络。径向基函数网络需要确定径向基函数的中心数,它们的接收场宽度和网络输出层的线性重量。在研究中介绍了估计接收领域的宽度的方法,以及径向基函数的中心的数量。后者基于广义自由度的概念。线性重量由最小二乘法确定。通过所提出的方法与四个水形气象数据集的实际值相比,预测比通过修复中心数量的传统方法更好。

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