基于神经网络和遗传算法的末敏弹系统效能参数优化设计

末敏弹是一种先进的新型弹药,由于其结构复杂,影响因素多,所以对其进行全面的系统优化设计十分困难.为此,本文利用神经网络的高度非线性映射能力和遗传算法的全局寻优能力,在了解了末敏弹工作原理的基础上,首先确定了一个优化设计方案,并根据该方案建立了一个末敏弹系统效能神经网络仿真模型,在此基础上,应用混合遗传算法对该仿真模型进行了优化设计,获得了影响系统效能的几个主要因素的最优搭配.经过对优化结果的分析,发现其与实际情况较为吻合,为末敏弹系统的效能研究提供了依据.

OPTIMAL DESIGN OF SYSTEM EFFICIENCY PARAMETERS ABOUT TERMINAL-SENSITIVE PROJECTILES BASED ON NEURAL NETWORK AND GENETIC ALGORITHM

Terminal-sensitive projectile is an advanced new-type of ammunition, having complex structure and a multiplicity of influencing factors, the overall optimal design to the terminal-sensitive projectile system is thus a very difficult work. Neural network and genetic algorithm were used in this paper, because of the highly non-linear reflecting capability of neural network and the overall optimizing ability of genetic algorithm. Working principle of terminal-sensitive projectile was introduced, and a project of optimal design was confirmed. Using theory of neural network and orthogonal experiments, a simulating model of terminal-sensitive projectile system efficiency was established. On this basis, using a hybrid genetic algorithm, an optimal design to the neural network simulation model was carried out. From it an optimal arrangement of several main factors affecting the system efficiency was obtained. Validation to the above optimal results was then done, and some conclusions about this optimal design formed, showing that the optimal arrangement of those influencing factors are wholly in accordance with the actual state, and that the method can provide scientific foundations for the future efficiency research of terminal-sensitive projectile systems.