Peacekeeping Equipment Support Spare Parts Demand Forecast

Abstract

In view of the increasingly complex international situation, the maintenance of world peace in the future, and the protection of the country's overseas interests, China will participate in more and more peacekeeping missions. In the face of the complexities of peacekeeping equipment and the complex and poor peacekeeping environment, and the maintenance of conflicts in maintenance, we must make use of it. Limited resources to meet the needs of peacekeeping equipment support spare parts. Firstly, we analyze the characteristics of peacekeeping missions, and have different equipment support requirements for different peacekeeping missions, and propose the concept of peacekeeping equipment support. Secondly, we propose the maintenance equipment support demand forecasting steps, based on l'SO-BP neural network, and the equipment guarantee prediction model. Historical data, through experiments to verify fhe validity and rationality of fhe model. The experimental results show that the maintenance model based on PSO-BP neural network can effectively predict the demand for maintenance equipment spare parts and improve the effectiveness of maintenance equipment.