支持向量机在航空兵部队油料消耗量预测中的应用

分析了支持向量机的基本原理及算法，确定了航空兵部队油料消耗量预测模型的样本输入量，构造了航空兵部队作战油料消耗量预测函数，采用LibSVM Matlab工具箱对模型进行编程求解，选用3个指标对预测结果进行评价。并以某空军航空兵部队油料消耗量为例，运用基于SVM的航空兵部队油料消耗量预测模型，对2009年演习的油料消耗量进行了预测，预测结果与实际值进行比较，预测精度高，为科学预测战场油料消耗量提供了科学定量的分析方法。

Application of support vector machine in oil consumption prediction model for aviation troops

This paper analyzes the basic principle of support vector machine, determines the sample inputs for oil consumption prediction model of aviation troops. The prediction function for aviation troops oil consumption is constructed, LibSVM Matlab toolbox is used to solve the model, and three indexes are selected to evaluated the prediction results. The oil consumption of one aviation troop is taken as an example. This aviation troops oil consumption prediction model is used to forecast the oil consumption in 2009 based on SVM, and the prediction results are compared with the actual value. It shows the high prediction accuracy, which provides scientific quantitative analytical method for prediction battlefield oil consumption.