Artillery Attacking Target Value Analysis Based on Gray Back Propagation Network Model

The target value analysis is the core task for artillery operational information processing.Firstly,the target value estimation index is established by analyzing the artillery target value.Secondly,aimed at the defect in traditional grey prediction model(GPM),the sample data are preprocessed to optimize GPM by using the mean modification strategy.By combining GPM with back propagation(BP)networks,the optimized gray neural network model is established.Finally,the main targets are chosen to form studying and testing samples to be modeled,tested and compared with grey BP networks.Simulation results prove that the proposed model is reasonable,effective and stable.