个人信息Personal Information
教授
硕士生导师
性别:男
毕业院校:吉林大学
学位:博士
所在单位:信息管理与信息系统研究所
学科:信息管理与电子政务
办公地点:管理楼518
电子邮箱:ywang@dlut.edu.cn
Comparison of Prim and Kruskal on Shanghai and Shenzhen 300 Index hierarchical structure tree
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论文类型:会议论文
发表时间:2009-11-07
收录刊物:EI、CPCI-S、Scopus
页面范围:237-+
关键字:Super metric Spaces; Hierarchical structure tree index; Minimum spanning tree(MST); Prim algorithm; Kruskal algorithm
摘要:This study's objective is to assess the performance of the common Prim and the Kruskal of the minimum spanning tree in building up super metric space. We proposed the use of complexity analysis and experimental methods to assess these two methods. After the analysis of the sample data of Shanghai and Shenzhen 300 index daily from the second half of 2005 to the second half of 2007, The results showed that when the number of shares is less than 100, judging from the space complexity, Kruskal algorithm is relatively superior to Prim algorithm; however, when the number of shares is greater than 100, from the time complexity's aspect, Prim algorithm is more superior. This study's conclusion indicates that matrix of Shanghai and Shenzhen 300 stock the inter-continental distance formed by the edge map more, so Prim better than Kruskal.