证据理论加权决策树在外包维修中的应用

李芳; 曾聪文

证据理论加权决策树在外包维修中的应用

引用本文：李芳,曾聪文.证据理论加权决策树在外包维修中的应用[J].计算技术与自动化,2010,(2):66-69

摘要点击次数: 1755

全文下载次数: 322

作者	单位
李芳,曾聪文	（桂林电子科技大学计算机与控制学院,广西桂林541004）

中文摘要:外包维修过程中产生的数据通常是模糊的，传统上很少按重要性分类，从这些数据仅仅能搜索到相关的不确定信息。将证据理论作为处理不确定数据的有力工具，提出用证据理论加权决策树算法对外包维修过程产生的不确定数据进行分类并挖掘出规则。实验结果表明本算法可有效的对外包维修数据进行分类，并可以生成可指导产品研发的规则。

中文关键词:证据理论决策树外包维修数据不确定

Application Evidence Theory Weighted Decision Tree Algorithm for Outsourced Maintenance

Abstract:Outsourced maintenance information can affect the product development sustainability, achievement transformation capacity and product quality. Data generated in the processes of outsourced maintenance are inherently vague and seldom classified according to their importance. From these data is only able to search the relevant uncertain information. Since evidence theory is a powerful tool can deal with uncertain data, this paper propose use evidence theory weighted decision tree algorithm to classify uncertain data generated form outsourced maintenance and to dig out the rules. The experimental results shows this algorithm can efficient classify uncertain data and generate rules which can guide the products research and development.

keywords:evidence theory decision tree outsourced maintenance data uncertain

查看全文 查看/发表评论 下载pdf阅读器