Event-Driven Model Predictive Control With Deep Learning for Wastewater Treatment Process-Reference-Cited by-同舟云学术

Event-Driven Model Predictive Control With Deep Learning for Wastewater Treatment Process

Published:2023-05 Issue:5 Volume:19 Page:6398-6407
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Wang Gongming¹^ORCID,Bi Jing²^ORCID,Jia Qing-Shan³^ORCID,Qiao Junfei¹^ORCID,Wang Lei⁴

Affiliation:

1. Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing Institute of Artificial Intelligence, Faculty of Information Technology, Beijing University of Technology, Beijing, China

2. Faculty of Information Technology, Beijing University of Technology, Beijing, China

3. Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing, China

4. School of Automation, Beijing Information Science and Technology University, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Scientific Research Foundation Project of Beijing Information Science and Technology University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/10116046/09780556.pdf?arnumber=9780556

Reference29 articles.

1. Soft-sensing of Wastewater Treatment Process via Deep Belief Network with Event-triggered Learning

2. Advanced decision control system for effluent violations removal in wastewater treatment plants

3. An Adaptive Deep Belief Network With Sparse Restricted Boltzmann Machines

4. Data-based composite control design with critic intelligence for a wastewater treatment platform

5. Application of neural networks for optimal-setpoint design and MPC control in biological wastewater treatment

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