基于改进型模糊神经网络的导弹武器系统生存能力评估

针对导弹武器系统生存能力评估问题,建立了评估的指标体系,给出了指标的隶属函数.利用BP神经网络的自学习、自适应、强容错性,并通过遗传算法（GA）优化BP神经网络的连接权重和阀值,弱化了评价中的人为因素,提高了评价结果的准确性和权威性,解决了BP神经网络存在落入局部最小点和收敛速度慢的问题.实例研究表明,遗传神经网络的评价模型具有有效性和可行性.

Survivability Evaluation Model of Missile Weapon System Based on Improved Fuzzy Neural Network

The index system for evaluating survivability of missile weapon is brought forward and the subordinate function of each index is given.An assessment model based on BP neural network whose thresholds and connection weights are optimized by genetic algorithm(GA-NN) is proposed in order to solve the problems.And the problems of the BP neural network trapping into local minimum point and low convergence speed are solved.Using the characteristics of self-learning,self-adaptive and efficient fault tolerant of BP ...