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An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-27
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
The concentration of alumina in the electrolyte is of great significance during the production of aluminum; it may affect the stability of aluminum reduction cell and the current efficiency.
However, the concentration of alumina is hard to be detected online because of the special circumstance in the aluminum reduction cell.
At present, there is lack of fast and accurate soft sensing methods for alumina concentration and existing methods can not meet the needs for online measurement.
In this paper, a novel soft sensing method based on a modified extreme learning machine (MELM) for online measurement of the alumina concentration is proposed.
The modified ELM algorithm is based on the enhanced random search which is called incremental extreme learning machine in some references.
It randomly chooses the input weights and analytically determines the output weights without manual intervention.
The simulation results show that the approach can give more accurate estimations of alumina concentration with faster learning speed compared with other methods such as BP and SVM.
American Psychological Association (APA)
Zhang, Sen& Chen, Xi& Yin, Yixin. 2015. An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1073357
Modern Language Association (MLA)
Zhang, Sen…[et al.]. An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection. Mathematical Problems in Engineering No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1073357
American Medical Association (AMA)
Zhang, Sen& Chen, Xi& Yin, Yixin. An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1073357
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073357