A Study on Instrumentation Results Analysis Using Artificial Neural Network in Tunnel Area

인공신경망을 이용한 터널시공 시 계측결과 분석에 관한 연구

Although it is important to reflect the accurate information of the ground condition in the tunnel design, the analysis and design are conducted by limited information because it is very difficult to get it practically on considering various geography and geotechnical condition. So construction management of information concept is required to manage immediately on the field condition because it is very time-consuming to establish the countermeasure of underground reinforcement and the pattern change of Bo. Therefore, when construction is on tunnel area, examination of accurate safety and prediction of behavior is performed to overcomes the limit of predicting behavior by using Artificial Neural Network(ANN) in this study. Firstly, the field data was secured. Secondly, suitable structure was made on multi-layer perceptrons among the ANN. Thirdly, learning algorithm-propagated applies to ANN. The data for the learn of field application using ANN was used by considering impact factors, which influenced the behavior of tunnel, and performing credibility analysis. crown displacement, spring displacement, subsurfacement, and rock bolt axial force are predicted at the tunnel construction and on-site application was confirmed by using ANN from analyzing and comparing with measurement value of on-site. In this study, the data from Seoul Highway $\bigcirc\bigcirc$ tunnel section was applied to the ANN Theory, and the analysis on the investigate value and the reasoning for the value associated with field application was performed.