지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.9
- 수록면
- 209 - 212 (4page)
이용수
초록· 키워드
오류제보하기
Compaction Grouting System(CGS) method, is a grouting technique that injects the noncurrent-mortar type grout into the ground, then the grout forms cylinder hardening structure, densifying the ground density, however, CGS method technology has applied to improving the soft ground widely at present. But this technology depends on the experience of construction and experiment, prior to construction, the constructors must grasp the improvement characteristic and practical situation. In addition, ask for a construction management, which can deal with the temporal and economical problems through numerical analysis rapidly. Therefore, this study focus on using artificial neural network for evaluating applicability of system which can measure the performance of soil improvement. As a result, the conjectural coefficient of determination is greater than 0.9 after training, shows a high correlation, and estimates that there is no differentiation as optimal structure, then calculates optimal structure by the untrained data. Calculated optimal structure using the coefficient of determination, 0.9 and model 5 and obtained that the maximum settlement is 0.166m, 0.172 and the minimum settlement is 0.008m, 0.001m by comparison with predicted settlement of the numerical analysis and artificial neural network
목차
SYNOPSIS
1. 서론
2. 학습 프로그램
3. 해석결과 및 분석
4. 결론
References
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UCI(KEPA) : I410-ECN-0101-2014-530-002858733