摘要
无人机费用预测是在装备研制设计阶段就必须考虑的重要问题。针对无人机费用预测小样本、具有不确定性等特点,提出了基于最小二乘支持向量机(LS-SVM,Least Squares Support Vector Machines)的无人机费用预测模型,并应用于研制费用、维修保障费用预测。应用结果表明,LS-SVM具有较高的费用预测精度。
Cost prediction of unmanned air vehicle （UAV） is an important and a considerable problem in the design and development phase of equipment. Since the cost prediction of UAV with few observations has some characteristics like uncertainty, etc. , a cost prediction model based on least squares support vector machines （LS - SVM） is presented and applied to both the development cost and the maintenance cost prediction problems in this paper. The results show that the model is of better precision in cost prediction.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2008年第1期22-25,共4页
Journal of Air Force Engineering University(Natural Science Edition)
关键词
无人机
最小二乘支持向量机
费用预测
小样本
unmanned air vehicle
least squares support vector machines
cost prediction
few observations
