An Optimization Design of Energy Consumption for Aluminum Smelting Based on a Multi-Objective Artificial Vulture Algorithm

An Optimization Design of Energy Consumption for Aluminum Smelting Based on a Multi-Objective Artificial Vulture Algorithm

In the process of regenerative aluminum smelting, the temperature of the furnace needs to be maintained between 700 and 850 by adjusting the setting parameters of the smelting furnace. The setting parameters are usually adjusted by manual work, and inaccuracies in manual operation can lead to wasted...

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Bibliografische gegevens
Hoofdauteurs: Jiayang Dai, Hangbin Liu, Yichu Zhang, Haofan Shi, Peirun Ling
Formaat: Artikel
Taal:English
Gepubliceerd in: MDPI AG 2025-01-01
Reeks:Metals
Onderwerpen:
aluminum smelting
optimization of energy consumption
multi-objective algorithm
Online toegang:https://www.mdpi.com/2075-4701/15/2/105

Internet

https://www.mdpi.com/2075-4701/15/2/105

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