摘要
为了实现航空装备的精确化保障,需要对航材备件数量进行预测,现有方法难以在小样本的条件下,准确地预测航材备件数量,为此提出了一种基于最小二乘支持向量机和信息熵的组合预测方法。首先,将基于最小二乘支持向量机的一元预测方法和多元预测方法相互结合,提出了一种组合预测模型;然后,使用信息熵理论对组合预测模型的权重系数进行优化;最后,给出了所提预测方法的计算步骤。实验结果表明,所提方法在预测航材备件数量时,具有较高的准确性。
In order to achieve precision support of the aviation equipment, the number of Aerial spare parts needs to be predicted. Because the existing methods are difficult to accurately predict the number with small samples, a novel combined method is proposed in this paper. Firstly, it combines the advantages of univariate and multivariate prediction methods which are both based on LSSVM. Then, weight coefficient of the combination prediction method is optimized based on entropy theory. The experiment results show that the proposed method has a higher accuracy in predicting the Aerial spare parts.
出处
《火力与指挥控制》
CSCD
北大核心
2012年第9期154-157,共4页
Fire Control & Command Control
基金
国家自然科学基金资助项目(71171199)
关键词
最小二乘支持向量机
信息熵
航材备件
一元回归
多元回归
组合预测
LSSVM,information entropy,aerial spare parts, univariate regression, multiple regression,combinational prediction
