A Novel Dynamic Operation Optimization Method Based on Multiobjective Deep Reinforcement Learning for Steelmaking Process-Reference-Cited by-同舟云学术

A Novel Dynamic Operation Optimization Method Based on Multiobjective Deep Reinforcement Learning for Steelmaking Process

Published:2023 Issue: Volume: Page:1-15
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Liu Chang¹^ORCID,Tang Lixin²^ORCID,Zhao Chenche³

Affiliation:

1. Ministry of Education, National Frontiers Science Center for Industrial Intelligence and Systems Optimization, and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China

2. National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, China

3. Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry, and the Liaoning Key Laboratory of Manufacturing System and Logistics Optimization, Northeastern University, Shenyang, China

Funder

Major Program of National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Post-Doctoral Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10050437.pdf?arnumber=10050437

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