基于支持向量机算法的虚拟脱靶量预测

为了提高防空高炮武器系统的射击精度问题,采用支持向量机(SVM)算法,建立了基于支持向量机的虚拟脱靶量预测模型,提出了预测方法,该算法可以通过对给定样本的学习,获得很好的预测未出现的样本,理论上比较科学,算法简单、易于实现,通过仿真实验验证了该算法对虚拟脱靶量预测的可用性和准确性,为火控系统精度的校正提供了一种有效的方法。

The Virtual Miss Shooting Forecasting Based on Support Vector Machine Algorithm

In order to improve the shooting accuracy of air-defense artillery weapons system, the paper imports the Support Vector Machine algorithm, establishes the model of the virtual miss distance forecasting based on the algorithm and introduces the way of forecasting. The algorithm can forecast the samples which have not appeared passed on the study of given samples, it is scientific in theory. The algorithm is simple and easy to implement. According to the experiment, it validates the algorithm's useable and veracity, provides an efficient way for the accuracy calibration of fire control system