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Application of genetic programming on statistical modeling

  • Kang Shun Li*
  • , Yuan Xiang Li
  • , Ming Duan Tang
  • , Ai Min Zhou
  • , Zhi Jian Wu
  • *此作品的通讯作者
  • Jiangxi University of Science and Technology
  • Wuhan University
  • China Aerospace Science and Industry Corporation

科研成果: 期刊稿件文章同行评审

摘要

An application of genetic programming in statistical modeling is proposed, which obviously improved the traditional regular methods of statistical modeling that could only obtain rough curve fitting and unsatisfactory results. Then, the estimating standard error and forecasting standard error were calculated and analyzed. By using the actual historical data from Statistics Yearbook of China and Statistics Yearbook of Jiangxi Province, China published in recent years, the automatic generated statistical model of economic forecasting by using genetic programming was established and the result indicates that the accuracy calculated by this statistical model is obviously much higher, compared with traditional methods such as linear regression, exponential regression and parabolic regression[3].

源语言英语
页(从-至)1597-1600
页数4
期刊Xitong Fangzhen Xuebao / Journal of System Simulation
17
7
出版状态已出版 - 7月 2005
已对外发布

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