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Georg H. Erharter ORCID

Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  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 (Mai 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 (Oktober 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 (Oktober 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 (Juli 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 (Februar 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 (Januar 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 (Dezember 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 (Oktober 2019).

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

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