類神經網路於地下開挖工程之應用

Application of Artificial Neural Network in Underground Constructions

陳錦清(J. C. Chern) ； 冀樹勇(S. Y. Chi) ； 俞旗文(C. W. Yu) ； 詹君治(J. C. Jan)

《地工技術》 91期 (2002/06) Pp. 39-46

https://doi.org/10.30140/SG.200206.0004

摘要

由於地下開挖工程之複雜性及影響因素之難以確實掌握，在目前地工技術發展之條件下，利用經驗指導設計是目前工程之主流。近年來快速發展的人工智慧技術，包括專家系統、案例推理系統及類神經網路，可綜合專家或工程案例經驗，有效解決新的工程問題。根據初步應用類神經網路於岩盤隧道支撐系統設計與軟地盤深開挖連續壁變形預測結果顯示，類神經網路已能利用以往工程案例經驗或施工監測資料，提供良好的工程設計建議或工程行為預測。

關鍵字

人工智慧 ； 類神經網路 ； 隧道支撐設計 ； 連續壁變形預測

並列摘要

Due to the complexity and uncertainty of factors affecting the underground construction, utilization of previous experiences as guidance in solving new problem is the major trend of engineering design for such projects. The rapidly developing artificial intelligence technologies, including expert system, case-based reasoning and artificial neural network, can provide an effective way of solving new problem by using experts' experiences or engineering case histories. Based on the preliminary results of applying the artificial neural network to rock tunnel support design and prediction of diaphragm wall deflection in braced excavation, it appears that the artificial neural network can be a viable method in providing design recommendation or predicting engineering performance by using the previous case histories or monitoring data.

並列關鍵字

artificial intelligence ； artificial neural network ； tunnel support design ； diaphragm wall deflection prediction