Projection Pursuit Regression Based on Hermite Polynomial for Atmospheric Corrosion Data Application

A Projection Pursuit Regression method by using Hermite Polynomial is put forward to make modeling and forcasting of corrosion data, because of small sample of acumulation data of metal material corrosion in atmosphere, Multi-dimensional Properties and Non-orthogonality of influence factors. Analyses and prediction of atmospheric corrosion data of a metal are made by using this method. Compared with PCA+SVM method, this method improves significantly the accuration of prediction and correctness of corrosion vehavior trend. The result proves that the Hermite Polynomial Projection Pursuit Regression method has great huge advantage in data analysis of steel corrosion in atmosphere.