28 citations · 31 across the 4 of their papers we have counts for
4 papers
Improved Long Short-Term Memory-based Wastewater Treatment Simulators for Deep Reinforcement Learning
Esmaeel Mohammadi, Daniel Ortiz-Arroyo, Mikkel Stokholm-Bjerregaard +2
Even though Deep Reinforcement Learning (DRL) showed outstanding results in the fields of Robotics and Games, it is still challenging to implement it in the optimization of industr…
Deep Learning Based Simulators for the Phosphorus Removal Process Control in Wastewater Treatment via Deep Reinforcement Learning Algorithms
Esmaeel Mohammadi, Mikkel Stokholm-Bjerregaard, Aviaja Anna Hansen +3
Phosphorus removal is vital in wastewater treatment to reduce reliance on limited resources. Deep reinforcement learning (DRL) is a machine learning technique that can optimize com…
Design, Modelling and Control of an Amphibious Quad-Rotor for Pipeline Inspection
Petar Durdevic, Shaobao Li, Daniel Ortiz-Arroyo
Regular inspections are crucial to maintaining waste-water pipelines in good condition. The challenge is that inside a pipeline the space is narrow and may have a complex structure…
Imagery Dataset for Condition Monitoring of Synthetic Fibre Ropes
Anju Rani, Daniel O. Arroyo, Petar Durdevic
Automatic visual inspection of synthetic fibre ropes (SFRs) is a challenging task in the field of offshore, wind turbine industries, etc. The presence of any defect in SFRs can com…