Study on Transportation and Replenishment Demand Forecasting Problem of Naval Warship

Abstract

To solve the problems of demand forecasting, the case-based reasoning (CBR) is used to create samples, and the least squares support vector machines (LSSVM) model is used as forecasting model, then the anti-air ammo demand forecasting in island offensive operation is taken as an empirical analysis. The result indicates that the samples created by case-based reasoning are available, and the forecasting results of different models are consilient but more accurate, this method can solve the problem of the lack of samples, so it is applicable to the combat supplies demand forecasting.