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Research on the Self-Repairing Model of Outliers in Energy Data Based on Regional Convergence

Author

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  • Nan Li

    (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Xunwen Zhao

    (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Hailin Mu

    (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Yimeng Li

    (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Jingru Pang

    (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Yuqing Jiang

    (School of Economics and Management, China University of Petroleum, Beijing 102249, China)

  • Xin Jin

    (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Zhenwei Pei

    (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

Abstract

The need for the statistical stability of data is increasing nowadays as the data resource has become a more and more important production factor. In this study, a set of general identification and correction models are established for data outlier modification. The research object we chose is the data of per capita energy consumption. Based on the joint diagnosis method of outliers and the regional convergence theory, the abrupt outliers are identified and corrected. The study finds that there is an outlier in the data of the Ningxia Hui Autonomous Region. According to the club grouping method, 30 provinces in China are divided into two clubs and the Ningxia Hui Autonomous Region is determined to be in the first club. We calculate the convergence rate and obtain the correction results combining the half-life cycle model.

Suggested Citation

  • Nan Li & Xunwen Zhao & Hailin Mu & Yimeng Li & Jingru Pang & Yuqing Jiang & Xin Jin & Zhenwei Pei, 2020. "Research on the Self-Repairing Model of Outliers in Energy Data Based on Regional Convergence," Energies, MDPI, vol. 13(18), pages 1-13, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4909-:d:415885
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    References listed on IDEAS

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