- 인공신경망 기법을 활용한 굴착공사 흙막이 변위량 예측에 관한 연구
- ㆍ 저자명
- 신한우,김광희,김용석,Shin. Han-Woo,Kim. Gwang-Hee,Kim. Young-Seok
- ㆍ 간행물명
- 한국건축시공학회지
- ㆍ 권/호정보
- 2007년|7권 3호|pp.131-137 (7 pages)
- ㆍ 발행정보
- 한국건축시공학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
To predict deep excavation wall movements is important in the urban areas considering the cost and the safety in construction. Failing to estimate deep excavation wall movements in advance causes too many problems in the projects. The purpose of this study is to propose the forecast model of deep excavation wall movements using artificial neural networks. The data of the Deep Excavation Wall Movements which were done form Long research is used of Artificial neural networks training and apply the real construction work measured data to the Artificial neural networks model. Applying the artificial neural networks to forecast the deep excavation wall movements can significantly contribute to identifying and preventing the accident in the overall construction work.