基于BP神经网络的防空保卫目标分类

Research on the classification of air defense objectives based on BP neural network

提出用BP神经网络模型对防空保卫目标进行分类的一种新方法。该方法建立分类评价的指标集,将分类的划分等级作为训练样本集,以指标的各等级标准值作为样本的输入特征值,建立多参数的BP神经网络防空保卫目标分类评价模型,然后用实例训练神经网络,得出了较合理的结论。

A new model of classification of air defense objectives based on BP neural network is put forward. The approach establishes the classification evaluation index system, and then regards the classified grades as training samples sets. The standard values of indexes are selected as input values of samples to establish multi-parameters classification model of air defense objectives based on BP neural network. At last an example is given to practice the BP neural network, and some kind of reasonable conclusion is obtained.