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MODERN TUNNELLING TECHNOLOGY 2019, Vol. 56 Issue (5) :35-41    DOI:
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A CBR-based Aided Decision Model for the Mountain Railway Tunnel Excavation Method
(1 School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031; 2 Key Laboratory of High-speed Railway Engineering of Ministry of Education, Southwest Jiaotong University, Chengdu 610031; 3 Key Laboratory of Transportation Tunnel Engineering of Ministry of Education, Southwest Jiaotong University, Chengdu 610031)
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Abstract In order to apply the experience of previous cases to decision making of the excavation methods in the Sichuan-Tibet railway tunnel to be built, an aided decision-making model for tunnel excavation method was established by the case-based reasoning (CBR) technology. It quantitatively expressed tunnel cases by several variables and determined the weight of each variable by OWA operator; then grey relational analysis was adopted for retrieval of similar cases and BP neural network was used to take train, furthermore the trained network was used for reasoning of the proposed tunnel schemes and a recommended scheme was obtained. This model was applied in the excavation scheme of Erlangshan tunnel on Sichuan-Tibet railway, which verified its effectiveness. The results show that the model can make full use of previous tunnel cases, a reasonable and feasible excavation scheme can be obtained by reasoning even if there is no detailed or definite information about topography, geology and so on.
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Articles by authors
LI Junda1
2 LI Yuanfu1
2 LI Shiqi1
3 LIU Kai1
3 WANG Guangkai1
2
KeywordsTunnel engineering   Case-based reasoning   Sichuan-Tibet railway   OWA operator   Grey relational analysis   BP neural network   Excavation method   Decision     
Abstract: In order to apply the experience of previous cases to decision making of the excavation methods in the Sichuan-Tibet railway tunnel to be built, an aided decision-making model for tunnel excavation method was established by the case-based reasoning (CBR) technology. It quantitatively expressed tunnel cases by several variables and determined the weight of each variable by OWA operator; then grey relational analysis was adopted for retrieval of similar cases and BP neural network was used to take train, furthermore the trained network was used for reasoning of the proposed tunnel schemes and a recommended scheme was obtained. This model was applied in the excavation scheme of Erlangshan tunnel on Sichuan-Tibet railway, which verified its effectiveness. The results show that the model can make full use of previous tunnel cases, a reasonable and feasible excavation scheme can be obtained by reasoning even if there is no detailed or definite information about topography, geology and so on.
KeywordsTunnel engineering,   Case-based reasoning,   Sichuan-Tibet railway,   OWA operator,   Grey relational analysis,   BP neural network,   Excavation method,   Decision     
Cite this article:   
LI Junda1, 2 LI Yuanfu1, 2 LI Shiqi1 etc .A CBR-based Aided Decision Model for the Mountain Railway Tunnel Excavation Method[J]  MODERN TUNNELLING TECHNOLOGY, 2019,V56(5): 35-41
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http://www.xdsdjs.com/EN/      或     http://www.xdsdjs.com/EN/Y2019/V56/I5/35
 
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