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Georg H. Erharter ORCID

The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Hansen, Tom F. / Erharter, Georg H. / Marcher, Thomas (2024): Towards reinforcement learning - driven TBM cutter changing policies. In: Automation in Construction, v. 165 (September 2024).

    https://doi.org/10.1016/j.autcon.2024.105505

  2. Erharter, Georg H. / Weil, Jonas / Bacher, Lisa / Heil, Frédéric / Kompolschek, Peter (2023): Building information modelling based ground modelling for tunnel projects – Tunnel Angath/Austria. In: Tunnelling and Underground Space Technology, v. 135 (May 2023).

    https://doi.org/10.1016/j.tust.2023.105039

  3. Morgenroth, Josephine / Unterlaß, Paul J. / Sapronova, Alla / Khan, Usman T. / Perras, Matthew A. / Erharter, Georg H. / Marcher, Thomas (2022): Practical recommendations for machine learning in underground rock engineering – On algorithm development, data balancing, and input variable selection. In: Geomechanics and Tunnelling, v. 15, n. 5 (October 2022).

    https://doi.org/10.1002/geot.202200047

  4. Erharter, Georg H. / Hansen, Tom F. (2022): Towards optimized TBM cutter changing policies with reinforcement learning. In: Geomechanics and Tunnelling, v. 15, n. 5 (October 2022).

    https://doi.org/10.1002/geot.202200032

  5. Erharter, Georg H. / Weil, Jonas / Tschuchnigg, Franz / Marcher, Thomas (2022): Potential applications of machine learning for BIM in tunnelling. In: Geomechanics and Tunnelling, v. 15, n. 2 (April 2022).

    https://doi.org/10.1002/geot.202100076

  6. Hansen, Tom F. / Erharter, Georg H. / Marcher, Thomas / Liu, Zhongqiang / Tørresen, Jim (2022): Improving face decisions in tunnelling by machine learning‐based MWD analysis. In: Geomechanics and Tunnelling, v. 15, n. 2 (April 2022).

    https://doi.org/10.1002/geot.202100070

  7. Erharter, Georg H. / Hansen, Tom F. / Liu, Zhongqiang / Marcher, Thomas (2021): Reinforcement learning based process optimization and strategy development in conventional tunneling. In: Automation in Construction, v. 127 (July 2021).

    https://doi.org/10.1016/j.autcon.2021.103701

  8. Erharter, Georg H. / Oberhollenzer, Simon / Fankhauser, Anna / Marte, Roman / Marcher, Thomas (2021): Learning decision boundaries for cone penetration test classification. In: Computer-Aided Civil and Infrastructure Engineering, v. 36, n. 4 (February 2021).

    https://doi.org/10.1111/mice.12662

  9. Erharter, Georg H. / Marcher, Thomas (2021): On the pointlessness of machine learning based time delayed prediction of TBM operational data. In: Automation in Construction, v. 121 (January 2021).

    https://doi.org/10.1016/j.autcon.2020.103443

  10. Erharter, Georg H. / Marcher, Thomas (2020): MSAC: Towards data driven system behavior classification for TBM tunneling. In: Tunnelling and Underground Space Technology, v. 103 (September 2020).

    https://doi.org/10.1016/j.tust.2020.103466

  11. Marcher, Thomas / Erharter, Georg H. / Winkler, Manuel (2020): Machine Learning in tunnelling – Capabilities and challenges. In: Geomechanics and Tunnelling, v. 13, n. 2 (April 2020).

    https://doi.org/10.1002/geot.202000001

  12. Erharter, Georg H. / Poscher, Gerhard / Sommer, Peter / Sedlacek, Christoph (2019): Geotechnical characteristics of soft rocks of the Inneralpine Molasse – Brenner Base Tunnel access route, Unterangerberg, Tyrol, Austria. In: Geomechanics and Tunnelling, v. 12, n. 6 (December 2019).

    https://doi.org/10.1002/geot.201900048

  13. Erharter, Georg H. / Marcher, Thomas / Reinhold, Chris (2019): Application of artificial neural networks for Underground construction – Chances and challenges – Insights from the BBT exploratory tunnel Ahrental Pfons. In: Geomechanics and Tunnelling, v. 12, n. 5 (October 2019).

    https://doi.org/10.1002/geot.201900027

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