Application research on genetic programming in the prediction of mining subsidence

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Xue-yang Sun and Yu-cheng Xia and Hui-min Qi and 
                 Liang Xiao",
  title =        "Application research on genetic programming in the
                 prediction of mining subsidence",
  booktitle =    "IEEE International Conference on Intelligent Computing
                 and Intelligent Systems, ICIS 2009",
  year =         "2009",
  month =        nov,
  volume =       "1",
  pages =        "29--32",
  keywords =     "genetic algorithms, genetic programming, data mining,
                 linear problems, mining subsidence prediction, data
                 mining, linear programming",
  DOI =          "doi:10.1109/ICICISYS.2009.5357941",
  abstract =     "Based on unique advantage of genetic programming on
                 solving linear problems, it was introduced into mining
                 subsidence. By using relevant data of mining subsidence
                 and the method of genetic programming, the nonlinear
                 relation between maximum amount of mining subsidence
                 and its influencing factors was set up. Compared with
                 practical data, the results showed that the prediction
                 accuracy of mining subsidence was improve effectively
                 by using the method than other prediction methods, and
                 a new idea for prediction of mining subsidence was
  notes =        "Also known as \cite{5357941} PDF severly broken Feb

Genetic Programming entries for Xue-yang Sun Yu-cheng Xia Hui-min Qi Liang Xiao