Machine learning meets process control: Unveiling the potential of LSTMc
Sign Up to like & getrecommendations! Published in 2024 at "AIChE Journal"
DOI: 10.1002/aic.18356
Abstract: In the past three decades, proportional‐integral/PI‐differential (PI/PID) controllers and model predictive controller (MPCs) have predominantly governed complex chemical process control. Despite their advancements, these approaches have limitations, with PI/PID controllers requiring scenario‐specific tuning and MPC… read more here.
Keywords: process control; control; machine learning; lstmc ... See more keywords
Reinforcement Learning Meets Wireless Networks: A Layering Perspective
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2020.3025365
Abstract: Driven by the soaring traffic demand and the growing diversity of mobile services, wireless networks are evolving to be increasingly dense and heterogeneous. Accordingly, in such large-scale and complicated wireless networks, optimal controlling is reaching… read more here.
Keywords: learning meets; meets wireless; reinforcement learning; layering perspective ... See more keywords
When Machine Learning Meets Wireless Cellular Networks: Deployment, Challenges, and Applications
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Communications Magazine"
DOI: 10.1109/mcom.001.1900664
Abstract: AI powered wireless networks promise to revolutionize the conventional operation and structure of current networks from network design to infrastructure management, cost reduction, and user performance improvement. Empowering future networks with AI functionalities will enable… read more here.
Keywords: learning meets; meets wireless; machine; cellular networks ... See more keywords
Federated Learning Meets Urban Opportunistic Crowdsensing in 6G Networks: Opportunities, Challenges, and Optimization Potentials
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Network"
DOI: 10.1109/mnet.2024.3520552
Abstract: 6G networks are envisioned to enable the Internet of Things (IoTs) and foster ubiquitous sensing. Urban opportunistic crowdsensing, which leverages participants carrying mobile sensing units (MSUs) in their daily activities to collect data, enables low-cost… read more here.
Keywords: urban opportunistic; opportunistic crowdsensing; federated learning; learning meets ... See more keywords
Machine learning meets pK a.
Sign Up to like & getrecommendations! Published in 2020 at "F1000Research"
DOI: 10.12688/f1000research.22090.1
Abstract: We present a small molecule pK a prediction tool entirely written in Python. It predicts the macroscopic pK a value and is trained on a literature compilation of monoprotic compounds. Different machine learning models were… read more here.
Keywords: machine; machine learning; learning meets;
Machine learning meets pK a
Sign Up to like & getrecommendations! Published in 2020 at "F1000Research"
DOI: 10.12688/f1000research.22090.2
Abstract: We present a small molecule pK a prediction tool entirely written in Python. It predicts the macroscopic pK a value and is trained on a literature compilation of monoprotic compounds. Different machine learning models were… read more here.
Keywords: machine; machine learning; learning meets;