Deep learning for electrolysis process anode effect prediction based on long short-term memory network and stacked denoising autoencoder

The anode effect is a common failure in the aluminium electrolysis industry. If the anode effect cannot be accurately predicted, it will cause increased energy consumption, harmful gas generation and even equipment damage in the aluminium electrolysis. In this paper, an anode effect prediction frame...

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Bibliographic Details
Published in:Rare metals Vol. 43; no. 12; pp. 6730 - 6741
Main Authors: Yin, Gang, Li, Yi-Hui, Yan, Fei-Ya, Quan, Peng-Cheng, Wang, Min, Cao, Wen-Qi, Xu, Heng-Quan, Lu, Jian, He, Wen
Format: Journal Article
Language:English
Published: Beijing Nonferrous Metals Society of China 01.12.2024
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ISSN:1001-0521, 1867-7185
Online Access:Get full text
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