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.
作者
邱璜
QIU Huang(College of Mechanical and Automotive Engineering,Anhui Vocational and Technical College of Industrial Economics,Hefei Anhui 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)。
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
FP-tree
new energy vehicle industry
international competitiveness
influencing factors
association rules
