한국지반공학회:학술대회논문집 (Proceedings of the Korean Geotechical Society Conference)
- 한국지반공학회 2005년도 춘계 학술발표회 논문집
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- Pages.1324-1334
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- 2005
터널거동 평가에서의 인공신경망 활용기법 연구
Prediction of Tunnel Behavior Using Artificial Neural Network
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Yoo, Chung-Sik
(Dept. of Civil and Envir. Engineering, Sungkyunkwan Univ.) ;
- Kim, Joo-Mi (Dept. of Civil and Envir. Engineering, Sungkyunkwan Univ.)
- 발행 : 2005.03.25
초록
This study investigated the applicability of the Artificial Neural Network (ANN) technique for prediction of tunnel behavior. For training data collection, a series of finite element analyses were conducted for actual tunnel project site. Using the data, optimimzed ANNs were developed through a sensitivity study on internal parameters. The developed ANNs can make tunneling related predictions such as tunnel crown settlement, shotcrete lining stress, ground surface settlement, and groundwater inflow rate. The results indicated that the developed ANNs can be used as an effective and efficient tool for tunnelling related prediction in practical tunneling situations.