Establishment of grey-neural network forecasting model of coal and gas outburst

摘要：

Effect factors on coal and gas outburst are analyzed using grey correlation method so as to determine the input parameters of artificial neural network (ANN). Then using the improved BP algorithm, we choose five dominant factors of grey correlation analysis as the input parameters to establish neural network model for forecasting coal and gas outburst. This network was trained by using the learning samples collected from the instances of typical coal and gas outburst mines in China. Meanwhile, we take coal and gas outburst instances of Yunnan Enhong coal mine as forecasting samples and compare the forecasting result from these samples with that from the conventional method, indicating that this model can meet the forecasting requirements of coal and gas outburst.

关键词： coal and gas outburst grey correlation analysis influencing factors forecasting grey-neural network

作者: Yang Sheng-qiang Sun Yan Chen Zu-yun Yu Bao-hai Xu Quan

作者单位: State Key Laboratory of Mine Resource and Safe Exploitation, School of Safety Engineering, China Uni State Key Laboratory of Mine Resource and Safe Exploitation, School of Safety Engineering, China Uni

会议类型: 国际会议

会议名称: The 6th International Conference on Mining Science & Technology ICMST 2009(第六届国际矿业科学技术大会)

会议地点: 徐州

会议语种:英文

页码: 1-6

在线出版日期: 2009-10-18（万方平台首次上网日期，不代表论文的发表时间）