一种多核神经网络集成的地震要素预测方法

为了提高地震要素的预测准确度,在同一个网络模型中构建多种不同类型的基核函数,对不同种径向基函数构建多核神经网络集成模型,以提高网络的精度.从确定最优径向基神经元数、适当加大训练的目标误差等多个方面加以优化,减小最小训练误差和提高预测精度.采用多元回归分析法,对样本进行拟合得到子预测的多元回归系数,对子预测模型进行多元回...

A Multi-core Radical Basis Neural Network Integrated Method for the Prediction of Earthquake Elements

For the purpose of improving the accuracy of predicting earthquake elements,basic core functions of various types were built on the same network model and multi-core neural network integration models were built for different types of radial basis functions to improve the accuracy of the network.The optimization was conducted from determining the amount of optimal radical basis neurons,increasing the target error of training appropriately and other aspects to reduce the minimum training error and increase the accuracy of prediction.Multiple regression analysis method was adopted to fit the samples so as to obtain the multiple regression coefficients of sub-predictions;the same method was adopted to conduct multiple regression integration on the sub-prediction models and perform anti-normalization treatment on the data,and eventually obtained the regression-integrated multi-core RBF(radical basis function)prediction model.The results indicated that the model of multiple regression prediction integration established by this multi-core neural network integration method for prediction of earthquake elements is capable of achieving the optimal fitting of actual value and predictive value as well as earthquake element predictive values of higher accuracy.