Complexity-Based Structural Optimization of Deep Belief Network and Application in Wastewater Treatment Process-Reference-Cited by-同舟云学术

Complexity-Based Structural Optimization of Deep Belief Network and Application in Wastewater Treatment Process

Published:2024-04 Issue:4 Volume:20 Page:6974-6982
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Wang Gongming¹^ORCID,Yuan Guanghui²^ORCID,Hu Zhiqiang³^ORCID,Chi Yuanying⁴^ORCID,Jia Qing-Shan⁵^ORCID,Qiao Junfei¹^ORCID

Affiliation:

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

2. Youcaiyongyong I. T. Company, Ltd., Rizhao Ecommerce Industrial Park, Rizhao, China

3. College of Mechanical and Architectural Engineering, Taishan University, Taian, China

4. School of Economics and Management, Beijing University of Technology, Beijing, China

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

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Beijing Natural Science Foundation

Humanities and Social Sciences of Ministry of Education Planning Fund of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9424/10492621/10415890.pdf?arnumber=10415890

Reference18 articles.

1. A Fast Learning Algorithm for Deep Belief Nets

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

3. Data-Driven Robust Adaptive Control With Deep Learning for Wastewater Treatment Process

4. Deep-Neural-Network-Based Economic Model Predictive Control for Ultrasupercritical Power Plant

5. Stochastic Control Framework for Determining Feasible Alternatives in Sampling Allocation