Study on Compound Genetic and Back Propagation Algorithm for Prediction of Coal and Gas Outburst Risk

  • Yaqin Wu
  • Kai Wang
  • Maoguang Wang
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 228)


Coal and gas outburst is a very complex phenomenon of dynamic disaster in coal mine. There exists a complex non-linear mapping relationship which could not be described with functions between outburst risk and its influential factors. Due to the originality and superiority of artificial neural network (ANN) for modeling and imitating non-linear problems, an ANN model for prediction of outburst risk is set up. Then through practical application, the performance of commonly applied Back Propagation (BP) network for outburst risk prediction is analyzed. Aimed at the weakness of BP algorithm and based on the overall searching characteristic of Genetic Algorithm (GA), an improved compound GA-BP algorithm is used to optimize the model, then both the performance of the network and the predicting reliability of the model are improved.

Key words

outburst risk prediction artificial neural network compound GA-BP algorithm 


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Copyright information

© International Federation for Information Processing 2006

Authors and Affiliations

  • Yaqin Wu
    • 1
  • Kai Wang
    • 2
  • Maoguang Wang
    • 1
    • 3
  1. 1.School of Computer Science & TechnologyChina University of Mining and TechnologyXuzhou, JiangsuChina
  2. 2.School of Mining & Safety EngineeringChina University of Mining and TechnologyXuzhou, JiangsuChina
  3. 3.Institute of Computing TechnologyChinese Academy of SciencesBeijingChina

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