| 基于人工神经网络的岩爆预测 |
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| 引用本文： | 陈海军,李能慧,倪德新,Shang Yuequan.基于人工神经网络的岩爆预测[J].岩石力学与工程学报,2003,22(5):762-768. |
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| 作者姓名： | 陈海军 李能慧 倪德新 Shang Yuequan |
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| 作者单位： | [1]中国矿业大学北京校区北京100083 [2]DepartmentofGeotechnicalEngineering,NanjingHydraulicResearchInstitute,Nanjing210024China [3]InstituteofEngineeringGeology,ChengduUniversityofTechnology,Chengdu610059China [4]InstituteofDisasterPrevention,ZhejianUniversity,Hangzhou310027China |
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| 基金项目： | Supported by Chinese National Natural Science Foundaion(49972091) |
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| 摘 要： | 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.
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| 关 键 词： | 人工神经网络 岩石力学 岩爆 预测 |
PREDICTION OF ROCKBURST BY ARTIFICIAL NEURAL NETWORK |
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| CHEN Haijun,Li Nenghui,NIE Dexin,Shang Yuequan.PREDICTION OF ROCKBURST BY ARTIFICIAL NEURAL NETWORK[J].Chinese Journal of Rock Mechanics and Engineering,2003,22(5):762-768. |
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| Authors: | CHEN Haijun Li Nenghui NIE Dexin Shang Yuequan |
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| Abstract: | 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. |
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| Keywords: | rock mechanics rockburst neural network underground rock engineering prediction |
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