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Deep Learning Based Operating Parameter Decision-Making Method for Optimal Penetration Rate

https://doi.org/10.2139/ssrn.4566720
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Development of a new hybrid ANN for solving a geotechnical problem related to tunnel boring machine performance
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Expert System for Applicability of Tunnel Boring Machines in Japan
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Intelligent assistant driving method for tunnel boring machine based on big data
inferredcites →https://doi.org/10.1016/0148-9062(84)91489-xopenalex-extracted
Factors affecting TBM penetration rates in sedimentary rocks
inferredcites →https://doi.org/10.1016/j.autcon.2021.103647openalex-extracted
Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network
inferredcites →https://doi.org/10.1016/j.autcon.2021.103880openalex-extracted
Decision support system for an intelligent operator of utility tunnel boring machines
inferredcites →https://doi.org/10.1016/j.ijrmms.2006.07.007openalex-extracted
Disc cutting tests in Colorado Red Granite: Implications for TBM performance prediction
inferredcites →https://doi.org/10.1016/j.measurement.2019.107244openalex-extracted
Performance prediction of tunnel boring machine through developing high accuracy equations: A case study in adverse geological condition
inferredcites →https://doi.org/10.1016/j.tust.2011.04.004openalex-extracted
A new hard rock TBM performance prediction model for project planning
inferredcites →https://doi.org/10.1016/j.tust.2012.02.012openalex-extracted
Study of various models for estimation of penetration rate of hard rock TBMs
inferredcites →https://doi.org/10.1016/j.tust.2016.01.034openalex-extracted
Application and development of hard rock TBM and its prospect in China
inferredcites →https://doi.org/10.1016/j.tust.2018.03.030openalex-extracted
A new method for selecting hard rock TBM tunnelling parameters using optimum energy: A case study
inferredcites →https://doi.org/10.1016/j.tust.2018.08.050openalex-extracted
Experimental study on wear of TBM disc cutter rings with different kinds of hardness
inferredcites →https://doi.org/10.1016/j.tust.2018.10.001openalex-extracted
A case study of TBM performance prediction using field tunnelling tests in limestone strata
inferredcites →https://doi.org/10.1016/s0886-7798(00)00029-8openalex-extracted
Advance rates of hard rock TBMs and their effects on project economics
inferredcites →https://doi.org/10.1109/access.2018.2821190openalex-extracted
Reliability-Based Performance Optimization of Tunnel Boring Machine Considering Geological Uncertainties
inferredcites →https://doi.org/10.1109/msp.2011.941097openalex-extracted
What Is a Savitzky-Golay Filter? [Lecture Notes]
inferredcites →https://doi.org/10.1007/s00158-016-1455-9openalex-snapshot
Multidisciplinary design optimization of tunnel boring machine considering both structure and control parameters under complex geological conditions
inferredcites →https://doi.org/10.1016/0886-7798(88)90029-6openalex-snapshot
Hard rock tunnel boring: Prognosis and costs
inferredcites →https://doi.org/10.1016/j.tust.2012.06.015openalex-snapshot
Analysis and prediction of TBM performance in blocky rock conditions at the Lötschberg Base Tunnel
inferredcites →https://doi.org/10.1016/j.tust.2020.103636openalex-snapshot
Tunnel boring machines (TBM) performance prediction: A case study using big data and deep learning
inferredcites →https://doi.org/10.1016/j.tust.2021.104054openalex-snapshot
Intelligent decision method for main control parameters of tunnel boring machine based on multi-objective optimization of excavation efficiency and cost
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