Based on the theory of virtual warehousing, the optimization system for equipment maintenance resources in virtual warehousing is established for the security task of equipment maintenance resources. According to the prediction problems on the spare parts requirements for equipment maintenance in this system, the demand forecasting model, based on the combination of rough sets and grey prediction, is adopted. The results of simulation experiment show that this method applied in equipment maintenance spare resources prediction is reliable and with accurate information. While, the relative error and absolute error of the predictive value and practical value are very small, which shows the prediction model is of high precision for the accurate effect prediction. As a result, this model and algorithum is proved to be effective to provide theoretical and practical support for equipment maintenance spare resources in information warfare.
