Research on Fault Diagnosis of Battlefield Resource Scheduling System Based on Quantum BP Neural Network
Jiao Yin, Ming Lyu, Jie Zhang · 2020
In the context of the rapid development of technology and the current military situation which cannot be slacked off, the battlefield resource scheduling and planning system is an important prevention system. Performing fault diagnosis research on this system can reduce the waste of traditional troubleshooting and improve the efficiency of fault diagnosis. The traditional BP neural network is easy to fall into the local minimum value in fault diagnosis, and the convergence speed is slow. To solve the above problems, a fault diagnosis model of the battlefield resource scheduling and planning system is established, and quantum computing is added to improve the performance of the BP neural network. At the same time, we combine with the expert knowledge base to diagnose system failures, and this method has certain reference value for the virtual battlefield scheduling system.