Application of deep neural networks in predicting the penetration rate of tunnel boring machines

• Published in: Bulletin of engineering geology and the environment Vol. 78; no. 8; pp. 6347 - 6360
• Main Authors: Koopialipoor, Mohammadreza, Tootoonchi, Hossein, Jahed Armaghani, Danial, Tonnizam Mohamad, Edy, Hedayat, Ahmadreza
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2019
• Subjects: Earth and Environmental Science; Earth Sciences; Foundations; Geoecology/Natural Processes; Geoengineering; Geotechnical Engineering & Applied Earth Sciences; Hydraulics; Nature Conservation; Original Paper; Penetration rate; Deep neural network; Tunnel boring machine; Artificial neural network

Performance prediction in mechanized tunnel projects utilizing a tunnel boring machine (TBM) is a prerequisite to accurate and reliable cost estimation and project scheduling. A wide variety of artificial intelligence methods have been utilized in the prediction of the penetration rate of TBMs. This...