非线性时间序列B样条优化网络预测模型及工业应用

为有效实现非线性时间序列的实时预测,建立了一种B样条优化网络预测模型。在网络结构的设计中,将各个样条基函数的权值参数和节点位置同时视为待优化的独立变量,并选择预测误差平方和为评价函数,设计了一种全局优化算法,对网络结构进行优化。工业仿真实验结果表明,所提出的优化网络预测模型具有较高的预测精度,而且结构简单,待优参数少,是一种有效的非线性时间序列预测方法。

An Optimized Model Based on Nonlinear Time Series for B-Spline Networks Prediction and Its Industrial Application

An optimizing model for B-spline networks prediction has been proposed for the effective realization of the real-time prediction based on nonlinear time series. A global optimization algorithm has been adopted for the optimization of the design of the network structure, with the weight parameters and node location of spline functions synchronous independent variables to be optimized. The industrial simulation results show that the proposed optimized model for networks prediction has a relatively higher prediction accuracy. With its structure much simpler and less parameters to be optimized, this is an effective prediction method based on nonlinear time series.