Application of GM(1,1)-BP Combined Model in Muzzle Velocity Prediction
Muzzle velocity is an important factor that affects the firing accuracy of artillery.How to accurately predict muzzle velocity and grasp the transient combat opportunity to strike targets precisely has become an important research direction.In the past,most of the muzzle velocity was predicted by a single prediction model.Although the calculation process is simple,the prediction accuracy is not ideal.In order to improve the prediction accuracy of the model,a combined prediction model is established based on the GM(1,1)and BP neural network prediction models with the principle of minimum the sum of error squares to predict the muzzle velocity.The prediction results show that the prediction accuracy of the combined model is higher than that of the other two single models.
万方数据
维普
