基于BP 神经网络的破片聚焦曲线优化

为解决战斗部预制破片的飞散方向控制这个复杂的非线性问题，基于大量试验和仿真数据，应用BP 神经 网络技术对破片飞散方向修正设计量进行预测，建立破片聚焦曲线优化设计系统，可对传统解析模型设计的破片聚 焦曲线进行自动优化。试验结果表明：优化后的聚焦曲线具有较高的破片聚焦效率，可有效减少破片聚焦曲线迭代 的试验次数。

Optimization of Fragment Focusing Curve Based on BP Neural Network

In order to solve the complicated nonlinear problem of the warhead preformed fragments dispersing direction control, based on a large number of experimental and simulation data, BP neural network technology was used to predict the design modification value of preformed fragments dispersing direction, and the fragment focusing curve optimization design system was established, which could automatically optimize the fragment focusing curve designed by the traditional analytical model. The test results show that the optimized focusing curve has high fragment focusing efficiency and can effectively reduce the iteration tests of fragment focusing curve.