- Toward machine learning based decision support for pre‐grouting in hard rock. Dans: civil engineering design, v. 6, n. 3 (23 septembre 2024). (2024):
- Towards reinforcement learning - driven TBM cutter changing policies. Dans: Automation in Construction, v. 165 (septembre 2024). (2024):
- Building information modelling based ground modelling for tunnel projects – Tunnel Angath/Austria. Dans: Tunnelling and Underground Space Technology, v. 135 (mai 2023). (2023):
- Practical recommendations for machine learning in underground rock engineering – On algorithm development, data balancing, and input variable selection. Dans: Geomechanics and Tunnelling, v. 15, n. 5 (octobre 2022). (2022):
- Towards optimized TBM cutter changing policies with reinforcement learning. Dans: Geomechanics and Tunnelling, v. 15, n. 5 (octobre 2022). (2022):
- Potential applications of machine learning for BIM in tunnelling. Dans: Geomechanics and Tunnelling, v. 15, n. 2 (avril 2022). (2022):
- Improving face decisions in tunnelling by machine learning‐based MWD analysis. Dans: Geomechanics and Tunnelling, v. 15, n. 2 (avril 2022). (2022):
- Reinforcement learning based process optimization and strategy development in conventional tunneling. Dans: Automation in Construction, v. 127 (juillet 2021). (2021):
- Learning decision boundaries for cone penetration test classification. Dans: Computer-Aided Civil and Infrastructure Engineering, v. 36, n. 4 (février 2021). (2021):
- On the pointlessness of machine learning based time delayed prediction of TBM operational data. Dans: Automation in Construction, v. 121 (janvier 2021). (2021):
- MSAC: Towards data driven system behavior classification for TBM tunneling. Dans: Tunnelling and Underground Space Technology, v. 103 (septembre 2020). (2020):
- Machine Learning in tunnelling – Capabilities and challenges. Dans: Geomechanics and Tunnelling, v. 13, n. 2 (avril 2020). (2020):
- Geotechnical characteristics of soft rocks of the Inneralpine Molasse – Brenner Base Tunnel access route, Unterangerberg, Tyrol, Austria. Dans: Geomechanics and Tunnelling, v. 12, n. 6 (décembre 2019). (2019):
- Application of artificial neural networks for Underground construction – Chances and challenges – Insights from the BBT exploratory tunnel Ahrental Pfons. Dans: Geomechanics and Tunnelling, v. 12, n. 5 (octobre 2019). (2019):