基于SVR-RFE的作战方案评估指标选择方法

Battle Scheme Evaluation Index Selection Based on SVR-RFE

针对作战方案评价指标权值确定过程存在不确定和主观性的问题,本文提出了基于支持向量回归机的线性和非线性递归特征消除法(SVR-RFE)。该方法利用权值向量和函数值作为SVR-RFE的特征选择标准,采用支持向量回归机(SVR)对特征选择前后的回归能力进行了分析比较。在某作战方案样本集上的仿真实验表明,线性和非线性SVR-RFE在作战方案数据集上的特征选择效果是一致的,在特征维度为50%左右时,SVR算法达到最优泛化性能。

In order to overcome the uncertainty and subjectivity in deciding the evaluation index weight of battle scheme,linear and non-linear SVR-RFE are proposed.The proposed methods make weight vector and the cost function value to act as feature selection criteria,and SVR is employed to compare the regression ability.The simulation experimental results on a battle scheme samples show that the same performance can be achieved by linear and non-linear SVR-RFE methods.The optimum generalization performance is achieved when index feature is about 50%.