Application research on genetic programming in the prediction of mining subsidence

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Sun:2009:ICIS,

• 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 provided.",
• notes = "Also known as \cite{5357941} PDF severly broken Feb 2010",

}

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

Citations