基于正交信号修正法的BP网络模型及其应用

介绍一种新的多变量数据预处理方法——正交信号修正(OSC)法，提出一种OSC与NIPALS算法结合的O-PLS算法，将该方法用于确定BP网络的基本结构，即确定BP网络的隐层数、节点数及其初始权值，由此建立了O-PLS-BP网络模型。并将它与标准的BP网络模型、PLS-BP网络模型进行比较。仿真结果表明，该算法的拟合和预测效果较好。

Back Propagation Network Model and Its Application Based on Orthogonal Signal Correction

A preprocessing method for multivariate data called Orthogonal Signal Correction(OSC) is introduced. This method combines O-PLS algorithm with nonlinear iterative partial least-squares algorithm. This algorithm is used to a fundamental structure of BP network. This paper proposes a novel BP network model based on O-PLS algorithm. The weights initialization and the member of hidden nodes are set by applying the loading weights and factor numbers of O-PLS algorithm. Performances of the BP, PLS, and PLS-BP are analyzed and compared for instance. The result shows that the PLS-BP has better fitting and forecast than BP, PLS.