Research on Projectile Range Prediction Based on SSA-BP Algorithm
Projectile launch parameters and meteorological conditions will affect range,and the influe-nce system is complex and difficult to predict accurately.Aiming at the problem that BP prediction al-gorithm will fall into local optimum due to improper initial weight and threshold value,a projectile range prediction model based on SSA algorithm optimized BP neural network is established.Projectile range is used as the output index,and projectile muzzle velocity,firing angle and wind conditions are selected as the input of influencing factors.After data pre-processing,projectile range is predicted.At the same time,the prediction accuracy of the BP neural network prediction model optimized by PSO and GA algorithms is compared with that of the SSA optimized BP neural network model to verify the prediction effect of the latter.The results show that the MAE,RMSE and MAPE of the SSA-BP predic-tion model are 10.4564 m,11.8313 m and 0.05813%,respectively,which are lower than the corre-sponding evaluation indexes of BP,PSO-BP and GA-BP prediction models.Therefore,the prediction accuracy of the SSA-BP model is higher than that of the BP,PSO-BP and GA-BP prediction models.The results can provide support for projectile range prediction and long range fire strike research.
external ballisticsprojectile range predictionBP neural networksparrow search algo-rithm
万方数据
维普
