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《Journal of Highway and Transportation Research and Development》 2004-07
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Study on Rockburst Intensity Prediction Method Based on Neural Network Theory

YANG Tao~1,SHEN Peiliang~2 (1.Department of Urban construction and Environment Engineering,University of Shanghai for Science and Technology, Shanghai 200093,China; 2.TBM Construction Branch of Shanghai Tunnel Engineering Co.,LTD.,Shanghai 200023,China)  
Rockburst is a kind of dynamic instability phenomenon of surrounding rock mass of underground space in high geostastic stress.The prediction of the rockburst intensity is one of the most important issues in the rockburst studies.Based on the neural network theory, a new rockburst intensity prediction model is established in this paper.The ratio of the maximum rock tangential stress to the compressive rock strength σ_θ/σ_c,the ratio of the compressive rock strength to the tensile rock strength σ_c/σ_tand the elastic energy index W_(et) are chosen as the criteria indexes.The BP network is trained using the collected data from any given standard for classified prediction of rockburst.A case study shows that the proposed model is feasible and has higher prediction accuracy.
【CateGory Index】: TU457
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