基于主成分分析和支持向量机的威胁判断模型

Threat Estimation Model Based on Principal Component Analysis and Support Vector Machine

目标威胁判断是防空作战中一项重要内容,在建立目标威胁模型时,首先要挑选特征参数,分析了影响威胁度的若干因素.这里采用主成分分析方法选择目标的特征参数;利用支持向量机建立了威胁判断模型,通过实例与神经网络法的结果进行了比较,结果表明支持向量机比较精确和简单.

The problem of estimating threat of target is important in air defence deployment. On estimating threat of target, the first thing is to select the character parameters of target. Several factors, which affect the threat of target, are discussed. The character parameters of target are selected based on principal component analysis. A threat estimation model is established by using support vector machine. The method is illustrated through examples and the results show that the support vector machine method is more accurate and simple than neural network method.