PREDICTION OF ROCKBURST BY ARTIFICIAL NEURAL NETWORK

被引：6

作者：

ChenHaijun LiNenghui NieDexin Shang Yuequan Department of Geotechnical Engineering Nanjing Hydraulic Research Institute Nanjing China Department of Geotechnical Engineering Tongji University Shanghai China Institute of Engineering Geology Chengdu University of Technology Chengdu China Institute of Disaster Prevention Zhejian University Hangzhou China ^{[210024
,200092
,610059
,310027
]}

机构：

来源：

岩石力学与工程学报 | 2003年 / 05期

关键词：

rock mechanics; rockburst; neural network; underground rock engineering; prediction;

D O I：

暂无

中图分类号：

TU457 [岩石稳定性分析];

学科分类号：

摘要：

<正> Based on the analysis of main causes of rockburst, the compressive strength, tensile strength, elastic energy index of rock and the maximum tangential stress of the cavern wall are chosen as the criterion indexes for rockburst prediction. A new approach using neural method is proposed to predict rockburst occurrence and its intensity. The prediction results show that it is feasible and appropriate to use artificial neural network model for rockburst prediction.

引用

页码：762 / 768

页数：7

共 4 条

[1] 国内外岩爆研究现状综述 [J].

徐林生 ;

王兰生 ;

李天斌 .

长江科学院院报, 1999, (04) :25-28+39

[2] 太平驿隧洞岩爆特征及防治措施 [J].

周德培，洪开荣 .

岩石力学与工程学报, 1995, (02) :171-178

[3] 岩爆的分形特征和机理 [J].

谢和平 ;

W.G.Pariseau .

岩石力学与工程学报, 1993, (01) :28-37

[4]

Use of mining and seismological parameters as premonitors of rockbursts[J] . C. Srinivasan,S.K. Arora,R.K. Yaji.International Journal of Rock Mechanics and Mining Sciences . 1997 (6)

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