[HTML][HTML] Towards reinforcement learning-driven TBM cutter changing policies
TF Hansen, GH Erharter, T Marcher - Automation in Construction, 2024 - Elsevier
Optimizing the cutter changing process for tunnel boring machines (TBMs) is crucial for
minimizing maintenance costs and maximizing excavation efficiency. This paper introduces …
minimizing maintenance costs and maximizing excavation efficiency. This paper introduces …
[HTML][HTML] Stochastic control of geological carbon storage operations using geophysical monitoring and deep reinforcement learning
K Noh, A Swidinsky - International Journal of Greenhouse Gas Control, 2024 - Elsevier
Geological carbon storage (GCS) is the process of injecting and storing carbon dioxide (CO
2) in the subsurface to reduce greenhouse gas emissions. Safe and profitable GCS …
2) in the subsurface to reduce greenhouse gas emissions. Safe and profitable GCS …
Modelling the dynamic performance of stormwater drainage systems integrated with infiltration trenches
B Çırağ, R Karagöz, AE Özer, AÖ Aydın… - Urban Water …, 2024 - Taylor & Francis
Urban flooding caused by urbanization and climate change is a critical challenge for city
infrastructures. Infiltration trenches are a green infrastructure system that collects and …
infrastructures. Infiltration trenches are a green infrastructure system that collects and …
High-accuracy slope stability analysis using data-driven and attention-based deep learning model
Y Zhou, H Fu, M Zhou, Y Zhao, J Chen - Earth Science Informatics, 2025 - Springer
Because of the abrupt occurrence and severe consequences of slope disasters, the analysis
of slope stability has been a focal point in the field of slope disaster prevention. Traditional …
of slope stability has been a focal point in the field of slope disaster prevention. Traditional …
Application of Deep Reinforcement Learning to Control Drainage in a Lab-Scale Geosystem
A Biniyaz, Z Liu - Geo-Congress 2024 - ascelibrary.org
This paper explores the deployment of deep reinforcement learning (DRL), a subset of
machine learning for automated decision-making, in a lab-scale geosystem. The developed …
machine learning for automated decision-making, in a lab-scale geosystem. The developed …