Application of Neural Network on Missile Storage Reliability Forecasting

To get better effect of missile storage reliability forecasting, the paper put forward a method based on neural network, and discussed steps of forecasting based on back propagation network and radial basis function network. At last, the storage reliability of one type ship-to-ship missile was forecasted based on BP network and RBF network. The result was suggested that both of the BP and RBF are suitable for Missile storage reliability forecasting, and the precision of the train goal is better by using RBF network. RBF network is more suitable for resolving this forecast problem.