Development of data-knowledge-driven predictive model and multi-objective optimization for intelligent optimal control of aluminum electrolysis process-Reference-Cited by-同舟云学术

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Development of data-knowledge-driven predictive model and multi-objective optimization for intelligent optimal control of aluminum electrolysis process

Published:2024-08 Issue: Volume:134 Page:108664
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Wang Jie,Xie Yongfang^ORCID,Xie Shiwen^ORCID,Chen Xiaofang

Publisher

Elsevier BV

Reference43 articles.

1. A modeling approach for time-dependent geometry applied to transient heat transfer of aluminum electrolysis cells;Allard;Metall. Mater. Trans. B,2019

2. A reference vector guided evolutionary algorithm for many-objective optimization;Cheng;IEEE Trans. Evol. Comput.,2016

3. MOPSO: a proposal for multiple objective particle swarm optimization;Coello,2002

4. State affine modeling and observer design for Hall-Héroult process;da Silva Moreira;IFAC-PapersOnLine,2020

5. Convection-diffusion model for alumina concentration in Hall-Héroult process;da Silva Moreira;IFAC-PapersOnLine,2022

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