Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Zhai:2006:JCUG,
  author =       "Shuhua Zhai and Qian Gao and Jianguo Song",
  title =        "Genetic Programming Approach for Predicting Surface
                 Subsidence Induced by Mining",
  journal =      "Journal of China University of Geosciences",
  year =         "2006",
  volume =       "17",
  number =       "4",
  pages =        "361--366",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, mining
                 induced surface subsidence, parameters",
  URL =          "http://www.wanfangdata.com.cn/qikan/periodical.Articles/dqkx-e/dqkx2006/0604/060413.htm",
  DOI =          "doi:10.1016/S1002-0705(07)60012-0",
  abstract =     "The surface subsidence induced by mining is a complex
                 problem, which is related with many complex and
                 uncertain factors. Genetic programming (GP) has a good
                 ability to deal with complex and nonlinear problems,
                 therefore genetic programming approach is proposed to
                 predict mining induced surface subsidence in this
                 article. First genetic programming technique is
                 introduced, second, surface subsidence genetic
                 programming model is set up by selecting its main
                 affective factors and training relating to practical
                 engineering data, and finally, predictions are made by
                 the testing of data, whose results show that the
                 relative error is approximately less than 10percent,
                 which can meet the engineering needs, and therefore,
                 this proposed approach is valid and applicable in
                 predicting mining induced surface subsidence. The model
                 offers a novel method to predict surface subsidence in
                 mining.",
  notes =        "a Department of Civil Engineering, University of
                 Science and Technology Beijing, Beijing 100083, China

                 b Department of Civil Engineering, University of
                 Science and Technology Beijing, Beijing 100083, China;
                 Key Laboratory of Ministry of Education on High
                 Efficient and Safety Mining for Metal Mines, Beijing
                 100083, China

                 c Department of Civil Engineering, University of
                 Science and Technology Beijing, Beijing 100083, China",
}

Genetic Programming entries for Shuhua Zhai Qian Gao Jianguo Song

Citations