Design of Soft-Sensing Model for Alumina Concentration Based on Improved Grey Wolf Optimization Algorithm and Deep Belief Network

To address the challenge of the real-time monitoring of alumina concentrations during the production process, this paper employs a Deep Belief Network (DBN) within the framework of deep learning to predict alumina concentration. Additionally, the improved Grey Wolf Optimizer (IGWO) is utilized to op...

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Bibliographic Details
Published in:	Processes Vol. 13; no. 3; p. 606
Main Authors:	Li, Jianheng, Chen, Zhiwen, Zhong, Xiaoting, Li, Xiangquan, Xia, Xiang, Liu, Bo
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.03.2025
Subjects:	Accuracy Algorithms Alumina Aluminum Aluminum oxide Back propagation Belief networks Comparative analysis Convergence Deep learning Efficiency Electrolysis Errors Fault diagnosis Genetic algorithms Liu Bo Mathematical optimization Measurement techniques Neural networks Optimization algorithms Parameters Particle swarm optimization R&D Real time Research & development Search algorithms Sustainable development Variables China
ISSN:	2227-9717, 2227-9717
Online Access:	Get full text
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