摘要
地面防空作战中,为有效地实现资源的优化配置,达到量敌用兵的目的,有必要对敌空袭规模进行预测。在遗传算法与BP神经网络结构模型相结合的基础上,利用遗传算法训练并优化神经网络权重,并对敌空袭规模进行预测。同时与BP算法和灰色系统理论模型进行了比较,经实例检验,计算结果与战场统计结果接近,并优于BP算法和灰色理论模型,具有良好的预测效果。
For the purpose of operational resource optimization,it is necessary to predict enemy air raid scale in the ground air defense operation. Based on combination of genetic algorithm and BP neural network structure model, a mode of enemy air raid scale is predicted by training and optimizing neural network weighting through the genetic alagorithm. The model is compared with the BP algorithm and grey system theoretic model. Its calculating result is approximate to the statistical result in the battlefield gotten form an example,and the model is superior to the BP algorithm and grey system theoretic model and has good effect on prediction.
出处
《火力与指挥控制》
CSCD
北大核心
2008年第1期81-83,99,共4页
Fire Control & Command Control
基金
军队重点课题资助项目(2006YZB-20)
关键词
地面防空
空袭规模
遗传算法
BP神经网络
预测模型
ground air defense ,air raid scale ,genetic algorithm ,BP neural network ,prediction model
