Evaluation method of operational effectiveness of terminal sensitive projectiles based on APSO BP neural network

DOI:	10.11809/bqzbgcxb2024.10.013
Keywords:	terminal sensitive projectiles; hit probability; performance evaluation; BP neural network; particle swarm optimization; APSO BP algorithm
Abstract:	In view of the complex structure, many influencing factors and difficulties in operational effectiveness analysis of terminal sensitive projectiles, the operational effectiveness evaluation index system was established by taking the hit probability of the terminal sensitive projectiles as the objective function.An operational effectiveness evaluation model based on APSO BP neural network was proposed, two models of BP neural network and PSO BP neural network were constructed for comparison, and the three models were simulated by Matlab. The results show that the running time of APSO BP neural network is 0.651 3 s, the mean square error is 0.003 2, and the correlation coefficient is 0.978 9. The running time of PSO BP neural network is 2.015 4 s, the mean square error is 0.007 5, and the correlation coefficient is 0.968 8. The running time of BP neural network is 14.137 5 s, the mean square error is 0.015 9, and the correlation coefficient is 0.890 0. APSO BP neural network evaluation model has shorter running time and higher prediction accuracy, which has important theoretical significance and practical value for the operational application of terminal sensitive projectiles.
Issue:	Vol. 45 No. 10 (2024)
Published:	2024-10-31
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