Proceedings of the Korean Geotechical Society Conference (한국지반공학회:학술대회논문집)

Korean Geotechnical Society (한국지반공학회)
권호 표지

Prediction of Tunnel Behavior Using Artificial Neural Network

터널거동 평가에서의 인공신경망 활용기법 연구

  • Yoo, Chung-Sik (Dept. of Civil and Envir. Engineering, Sungkyunkwan Univ.) ;
  • Kim, Joo-Mi (Dept. of Civil and Envir. Engineering, Sungkyunkwan Univ.)
  • 유충식 (성균관대학교 공과대학 토목환경공학과) ;
  • 김주미 (성균관대학교 공과대학 토목환경공학과)
  • Published : 2005.03.25
Download PDF
⟨ Previous Next ⟩

Abstract

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.

Keywords