基于数值试验的山岭隧道围岩稳定性GIS-SVM预测

doi:10.13722/j.cnki.jrme.2019.0276

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Abstract The geological conditions in mountainous areas are complex and changeable，thus accidents of tunnel surrounding rock occur frequently. It is of great significance to accurately predict and evaluate the stability of surrounding rock in the whole course of tunnel. Therefore，by combining the numerical simulation test，the support vector machine(SVM) and GIS technology，this paper proposed a GIS-SVM combined method for visual prediction and evaluation of the surrounding rock stability of the tunnel. Firstly，on basis of the existing research results，seven evaluation indexes of surrounding rock stability including elasticity modulus and Poisson’s ratio were selected，SVM training samples were obtained by using the strength reduction method and the numerical simulation in FLAC3D. Afterwards，the SVM evaluation model was established based on the sample. Finally，based on the GIS platform，the established SVM evaluation model was simulated to the Baishiyi tunnel of Zhongliang mountain in Chongqing. The research area was divided into six grades：very stable，stable，relatively stable，basically stable，under stable and unstable，and then the stability prediction and evaluation map of the tunnel was formed. Furthermore，the effectiveness of the prediction was verified by the comparative analysis of the various bad geological conditions. Research results are expected to provide scientific grounds which can ensure the safety and stability of mountain tunnel at the construction and operation stage.

Key words： tunnelling engineering mountain tunnel numerical experiment support vector machine(SVM) geographic information system(GIS) combined evaluation method surrounding rock stability

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	Articles by authors
	WEN Haijia1
	2
	3
	HUANG Jianhao3
	YUAN Xinghan4
	XIE Peng5
	XUE Jingyuan3

Cite this article:

WEN Haijia1,2,3, et al. GIS-SVM prediction of surrounding rock stability in mountain tunnel based on numerical experiment[J]. , 2020, 39(S1): 2920-2929.

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http://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2019.0276 OR http://rockmech.whrsm.ac.cn/EN/Y2020/V39/IS1/2920

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