基于FP-tree的新能源汽车产业国际竞争力影响因素关联挖掘算法  

Association Mining Algorithm of Competitiveness International Influencing Factors for New Energy Vehicle Industry Based on FP-Tree

作　　者：邱璜[1] QIU Huang(College of Mechanical and Automotive Engineering,Anhui Vocational and Technical College of Industrial Economics,Hefei Anhui 230039)

机构地区：[1]安徽工业经济职业技术学院机械与汽车工程学院,安徽合肥230039

出　　处：《湖北理工学院学报》2024年第4期54-57,80,共5页Journal of Hubei Polytechnic University

基　　金：安徽省高校人文社科重点项目(项目编号:SK2021A1123)。

摘　　要：为充分挖掘新能源汽车产业国际竞争力影响因素、探究价值增长点,提出了基于FP-tree的影响因素关联挖掘算法。通过构建国际竞争力各指标影响因素的关联规则,分析任意事务数据集中的关联数据,利用最小支持度参数minsup按照从上到下的方式搜索,确定最长的频繁项目集,采用FP-tree关联频繁项目集,设定分支关联性挖掘标准,实现了新能源汽车产业国际竞争力影响因素的挖掘。测试结果表明,设计算法的最小支持度和数据关联挖掘时间较短,置信度分析具有较高的稳定性。In order to fully explore the influencing factors of the international competitiveness of the new energy automobile industry and explore the value growth point,an association mining algorithm based on the FP-tree for the influencing factors of the international competitiveness of the new energy automobile industry is proposed.The minimum support parameter minsup is used to search from top to bottom to determine the longest frequent itemset.Then FP-Tree is used to associate frequent itemsets set branch correlation mining standards and explore the factors influencing the international competitiveness of the new energy vehicle industry.The test results show that the minimum support and data association mining time of the designed algorithm are short,and the confidence analysis has high stability.

关 键 词：FP-TREE 新能源汽车产业 国际竞争力 影响因素 关联规则 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]