RS_SVM在装备维修费用预测中的应用  

Applications of RS_SVM in equipment maintenance costs prediction

作　　者：周辅疆[1,2] 田伟峰[1] 朱小冬[1] 

机构地区：[1]军械工程学院装备指挥与管理系,石家庄050003 [2]镇江船艇学院,江苏镇江212003

出　　处：《计算机工程与应用》2010年第31期222-224,共3页Computer Engineering and Applications

摘　　要：在分析粗糙集和支持向量机原理及各自的优缺点基础上,提出将粗糙集与支持向量机相结合的方法,构建了基于粗糙集与支持向量机(RS-SVM)的预测模型,并将该模型应用于装备维修费用预测。以某装备维修费用为例进行实例验证,计算结果表明,这种方法比其他方法有更好的预测精度。Based on analyzing advantage and defect of the Rough Sets（RS） theory and Support Vector Machines（SVM）,a minimum decision network combining RS and SVM in intelligence is brought forward.A kind of forecasting model based on RS-SVM is designed and applied on the prediction of equipment maintenance costs.An example of the prediction of equipment maintenance costs is given, and the result shows that the method can bring less error and better predicted precision compared with other methods.

关 键 词：粗糙集 支持向量机 装备维修费用 预测 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]