This paper improved the known study for technical progress in Malmquist productivity index calculating. In the method, all the possible movements for decision making units （DMUs） are listed, and the condition that s...This paper improved the known study for technical progress in Malmquist productivity index calculating. In the method, all the possible movements for decision making units （DMUs） are listed, and the condition that several DMUs lie on the productivity frontier is analyzed. The dynamic efficiencies of Chinese listed power companies from 1997 to 2006 were evaluated. The empirical results indicate that the improved method is effective.展开更多
SCIENCE CITATION INDEX EXPANDED-NEUROSCIENCES-JOURNAL LIST Total journals： 245 1. ACS CHEMICAL NEUROSCIENCE Monthly ISSN： 1948-7193 AMER CHEMICAL SOC, 1155 16TH ST, NW, WASHINGTON, USA, DC, 20036 · Science Cita...SCIENCE CITATION INDEX EXPANDED-NEUROSCIENCES-JOURNAL LIST Total journals： 245 1. ACS CHEMICAL NEUROSCIENCE Monthly ISSN： 1948-7193 AMER CHEMICAL SOC, 1155 16TH ST, NW, WASHINGTON, USA, DC, 20036 · Science Citation Index Expanded · BIOSIS Previews展开更多
针对在海量数据中频繁项集挖掘耗时问题,近年来提出的N-List结构可有效提高挖掘效率。基于N-List提出一种新的频繁项集挖掘算法HNSFI(Hash table and subsume frequent itemsets mining based on N-List)。该算法利用PPC-tree生成N-List...针对在海量数据中频繁项集挖掘耗时问题,近年来提出的N-List结构可有效提高挖掘效率。基于N-List提出一种新的频繁项集挖掘算法HNSFI(Hash table and subsume frequent itemsets mining based on N-List)。该算法利用PPC-tree生成N-List,引入哈希表存储N-List表示的项集,加快N-List相交操作运算时间;引入包含因子概念,利用其性质通过组合方法可以直接生成部分频繁项集,进一步提高算法时间性能。在三种不同的数据集上对该算法进行了测试和分析,实验结果表明在稠密数据集中该算法的时间性能是最优的。展开更多
This study seeks to evaluate the comparative productivity of 32 listed tourism companies which are the main suppliers of China tourism, using the popular methodology known as the data envelopment analysis(DEA). This s...This study seeks to evaluate the comparative productivity of 32 listed tourism companies which are the main suppliers of China tourism, using the popular methodology known as the data envelopment analysis(DEA). This study analyzes the productivity of listed tourism companies from business and region aspects based on the calculation of Malmquist index. The results show that(1) the overall productivity is non-effi cient(0.954);(2) the productivity of accommodation and catering is biggest, which shows the tourism develops quickly with supports from technology;(3) the productivity in western China is highest, where the economy and tourism attraction are better than other regions; and(4) the effi ciency differences among the listed tourism companies are not signifi cant, and they attribute to the scale effi-ciency, that is the input of the fi nance, resource, talents and policy.展开更多
文摘This paper improved the known study for technical progress in Malmquist productivity index calculating. In the method, all the possible movements for decision making units （DMUs） are listed, and the condition that several DMUs lie on the productivity frontier is analyzed. The dynamic efficiencies of Chinese listed power companies from 1997 to 2006 were evaluated. The empirical results indicate that the improved method is effective.
文摘SCIENCE CITATION INDEX EXPANDED-NEUROSCIENCES-JOURNAL LIST Total journals： 245 1. ACS CHEMICAL NEUROSCIENCE Monthly ISSN： 1948-7193 AMER CHEMICAL SOC, 1155 16TH ST, NW, WASHINGTON, USA, DC, 20036 · Science Citation Index Expanded · BIOSIS Previews
文摘针对在海量数据中频繁项集挖掘耗时问题,近年来提出的N-List结构可有效提高挖掘效率。基于N-List提出一种新的频繁项集挖掘算法HNSFI(Hash table and subsume frequent itemsets mining based on N-List)。该算法利用PPC-tree生成N-List,引入哈希表存储N-List表示的项集,加快N-List相交操作运算时间;引入包含因子概念,利用其性质通过组合方法可以直接生成部分频繁项集,进一步提高算法时间性能。在三种不同的数据集上对该算法进行了测试和分析,实验结果表明在稠密数据集中该算法的时间性能是最优的。
基金supported by the project of Shaanxi Normal University(Grant No.999521)Xianyang Normal University(Grant Nos.11XSYK316,201002001)
文摘This study seeks to evaluate the comparative productivity of 32 listed tourism companies which are the main suppliers of China tourism, using the popular methodology known as the data envelopment analysis(DEA). This study analyzes the productivity of listed tourism companies from business and region aspects based on the calculation of Malmquist index. The results show that(1) the overall productivity is non-effi cient(0.954);(2) the productivity of accommodation and catering is biggest, which shows the tourism develops quickly with supports from technology;(3) the productivity in western China is highest, where the economy and tourism attraction are better than other regions; and(4) the effi ciency differences among the listed tourism companies are not signifi cant, and they attribute to the scale effi-ciency, that is the input of the fi nance, resource, talents and policy.
