Combination Forecasting Method of Ship Equipment Maintenance Cost withPrincipal Component Analysis

Using regression-based combination forecasting method to forecast ship equipment maintenance cost has fundamental drawback that the number of methods available is bigger than the cost samples'，making it insufficient to estimate the regression coefficient. This paper proposed to apply the Principal Component Analysis（PCA）on the results which obtained by the individual forecast method prior to building regression-based combination model of a ship equipment maintenance cost forecast，and then the regression model of a realistic ship equipment maintenance cost on selected principal components was established，further，the forecast combination model based on PAC was presented. Meanwhile，in the process of PCA，there was some subjectivity in deciding the number of principal components according as cumulate contribution rate of principal components，so we took the Akaike's Information Criterion（AIC）as a substitution. Finally an exampal was used to analyze and validate the performance of the above mentioned method. The results show that the presented method not only can solve the problem that the number of forecasting models is in excess of the sample's in the regression-based combination forecasting of ship equipment maintenance cost，but also can solve the collinear between individual forecast method. And the performance of the presented method obviously superior to the usual combined forecasting models.