›› 2003, Vol. 24 ›› Issue (6): 1016-1020.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Prediction of rockburst by genetic algorithm-neural network

YIN Guang-zhi1, 2, DAI Gao-fei1, 3, YAN He1, 2, WEI Zuo-an1, 2   

  1. 1. Key Laboratory of the Exploitation of Southwest Resources & the Environmental Hazards Control Engineering, Ministry of Education, Chongqing University, Chongqing 400044, China; 2. College of Resources and Environmental Sciences, Chongqing University, Chongqing 400004, China; 3. Department of Geotechnical Engineering, Tongji University, Shanghai 200092, China
  • Received:2002-07-22 Online:2003-12-10 Published:2014-08-19

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Abstract: Based on the research of mining circumstances and geological conditions of rockburst in Yanshitai coal mine, the influence factors of rockburst are provided. Because of the shortage of traditional methods to forecast rockburst, the method based on the back propagation neural network and genetic algorithm is applied to predict rockburst through reduction training time and instability in network training in Yanshitai coal mine. The results show that it is an effective method to predict rockburst and it can be applied to similar engineerings.

Key words: rockburst, back propagation neural network, genetic algorithm

CLC Number: 

  • TD 265
  • Please send e-mail to pingzhou3@126.com if you would like to read full paper in English for free. Parts of our published papers have English translations.
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