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针对扫雷作战仿真中的参数优化问题,论述了BP神经网络和遗传算法在扫雷参数优化中的应用。首先对某作战背景下的扫雷作战效能进行了详细分析,给出了雷区清扫率的计算方法;然后利用BP神经网络建立了扫雷参数与雷区清扫率之间的数学模型;最后通过遗传算法对扫雷参数进行优化研究。研究结果表明,该方法能够较精确地建立扫雷作战效能模型,并能快速搜索到最优扫雷参数组合条件。
Aiming at the parameter optimization problem in the mine clearance operation simulation, the application of BP neural network and genetic algorithm in mine clearance parameter optimization is discussed. Firstly, a detailed analysis of the effectiveness of mine clearance operations under a certain operational background is given, and the calculation method of mine clearance rates is given. Then, a mathematical model between mine clearance parameters and mine clearance rates is established by using BP neural network. Finally, Optimization of mine clearance parameters. The results show that this method can establish the effectiveness model of mine clearance operations more accurately, and can search the optimal combination of mine clearance parameters rapidly.