| Artificial neural network based online rockmass behavior classification of TBM data GH Erharter, T Marcher, C Reinhold Information Technology in Geo-Engineering: Proceedings of the 3rd …, 2020 | 38 | 2020 |
| On the pointlessness of machine learning based time delayed prediction of TBM operational data GH Erharter, T Marcher Automation in Construction 121, 103443, 2021 | 36 | 2021 |
| MSAC: Towards data driven system behavior classification for TBM tunneling GH Erharter, T Marcher Tunnelling and Underground Space Technology 103, 103466, 2020 | 34 | 2020 |
| Machine Learning in tunnelling–Capabilities and challenges T Marcher, GH Erharter, M Winkler Geomechanics and Tunnelling 13 (2), 191-198, 2020 | 32 | 2020 |
| Application of artificial neural networks for Underground construction–Chances and challenges–Insights from the BBT exploratory tunnel Ahrental Pfons GH Erharter, T Marcher, C Reinhold Geomechanics and Tunnelling 12 (5), 472-477, 2019 | 30 | 2019 |
| Reinforcement learning based process optimization and strategy development in conventional tunneling GH Erharter, TF Hansen, Z Liu, T Marcher Automation in Construction 127, 103701, 2021 | 26 | 2021 |
| Comparison of artificial neural networks for TBM data classification GH Erharter, T Marcher, C Reinhold ISRM Congress, ISRM-14CONGRESS-2019-293, 2019 | 19 | 2019 |
| Learning decision boundaries for cone penetration test classification GH Erharter, S Oberhollenzer, A Fankhauser, R Marte, T Marcher Computer‐Aided Civil and Infrastructure Engineering 36 (4), 489-503, 2021 | 14 | 2021 |
| Cone penetration test dataset Premstaller Geotechnik S Oberhollenzer, M Premstaller, R Marte, F Tschuchnigg, GH Erharter, ... Data in Brief 34, 106618, 2021 | 14 | 2021 |
| Building information modelling based ground modelling for tunnel projects–Tunnel Angath/Austria GH Erharter, J Weil, L Bacher, F Heil, P Kompolschek Tunnelling and Underground Space Technology 135, 105039, 2023 | 8 | 2023 |
| On the effect of shield friction in hard rock TBM excavation GH Erharter, R Goliasch, T Marcher Rock Mechanics and Rock Engineering 56 (4), 3077-3092, 2023 | 6 | 2023 |
| Machine learning–an approach for consistent rock glacier mapping and inventorying–example of Austria GH Erharter, T Wagner, G Winkler, T Marcher Applied Computing and Geosciences 16, 100093, 2022 | 6 | 2022 |
| Stochastic 3D modelling of discrete sediment bodies for geotechnical applications GH Erharter, F Tschuchnigg, G Poscher Applied Computing and Geosciences 11, 100066, 2021 | 6 | 2021 |
| Practical recommendations for machine learning in underground rock engineering–On algorithm development, data balancing, and input variable selection J Morgenroth, PJ Unterlaß, A Sapronova, UT Khan, MA Perras, ... Geomechanics and Tunnelling 15 (5), 650-657, 2022 | 4 | 2022 |
| Improving face decisions in tunnelling by machine learning‐based MWD analysis TF Hansen, GH Erharter, T Marcher, Z Liu, J Tørresen Geomechanics and Tunnelling 15 (2), 222-231, 2022 | 4 | 2022 |
| A new parameter for TBM data analysis based on the experience of the Brenner Base Tunnel excavation G Heikal, GH Erharter, T Marcher IOP Conference Series: Earth and Environmental Science 833 (1), 012158, 2021 | 4 | 2021 |
| Identifying rock loads on TBM shields during standstills (non-advance-periods) PJ Unterlass, GH Erharter, T Marcher Geotechnical and Geological Engineering 41 (1), 75-89, 2023 | 3 | 2023 |
| Towards optimized TBM cutter changing policies with reinforcement learning GH Erharter, TF Hansen Geomechanics and Tunnelling 15 (5), 665-670, 2022 | 3 | 2022 |
| Potential applications of machine learning for BIM in tunnelling GH Erharter, J Weil, F Tschuchnigg, T Marcher Geomechanics and Tunnelling 15 (2), 216-221, 2022 | 3 | 2022 |
| UAV-based discontinuity analyses and rock fall source mapping in Alpine Terrain (Pletzachkogel/Tyrol/Austria) GH Erharter, DS Kieffer, C Prager IAEG/AEG Annual Meeting Proceedings, San Francisco, California, 2018-Volume …, 2019 | 3 | 2019 |
Tom F. HansenSenior Engineer at Norwegian Geotechnical InstituteVerified email at ngi.no
