Deep reinforcement learning in production systems: a systematic literature review
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …
challenges for production systems. These not only have to cope with an increased product …
Reinforcement Learning in Process Industries: Review and Perspective
This survey paper provides a review and perspective on intermediate and advanced
reinforcement learning (RL) techniques in process industries. It offers a holistic approach by …
reinforcement learning (RL) techniques in process industries. It offers a holistic approach by …
A Deep Reinforcement Learning Approach to Sensor Placement under Uncertainty
A Jabini, EA Johnson - IFAC-PapersOnLine, 2022 - Elsevier
Optimal sensor placement is critical for enhancing the effectiveness of monitoring dynamical
systems. Deterministic solutions do not reflect the effects of input and parameter uncertainty …
systems. Deterministic solutions do not reflect the effects of input and parameter uncertainty …
[PDF][PDF] Oil Production Optimization Under Gas-Coning Conditions by Well-Cycling and Mixed-Integer Programming
JS Rodriguez, F Trespalacios, A Mishra, K Zorn… - folk.ntnu.no
When oil is produced from a reservoir, a pressure gradient is introduced throughout the
formation. Such pressure gradient can induce upward and downward movement of water …
formation. Such pressure gradient can induce upward and downward movement of water …
[PDF][PDF] Reinforcement Learning and Data Analytics for Dynamic Risk Analysis in Oil Exploration Activities
GK Sinha - J Artif Intell Mach Learn & Data Sci 2022 - urfjournals.org
Reinforcement Learning (RL) along with Data Analytics (DA) are rapidly evolving sectors
that holds immense promise in improving decision-making in intricate and changeable …
that holds immense promise in improving decision-making in intricate and changeable …