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A Novel Improved ELM Algorithm for a Real Industrial Application
Joint Authors
Zhang, Sen
Zhang, Hai-Gang
Yin, Yi-Xin
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-16
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
It is well known that the feedforward neural networks meet numbers of difficulties in the applications because of its slow learning speed.
The extreme learning machine (ELM) is a new single hidden layer feedforward neural network method aiming at improving the training speed.
Nowadays ELM algorithm has received wide application with its good generalization performance under fast learning speed.
However, there are still several problems needed to be solved in ELM.
In this paper, a new improved ELM algorithm named R-ELM is proposed to handle the multicollinear problem appearing in calculation of the ELM algorithm.
The proposed algorithm is employed in bearing fault detection using stator current monitoring.
Simulative results show that R-ELM algorithm has better stability and generalization performance compared with the original ELM and the other neural network methods.
American Psychological Association (APA)
Zhang, Hai-Gang& Zhang, Sen& Yin, Yi-Xin. 2014. A Novel Improved ELM Algorithm for a Real Industrial Application. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-501090
Modern Language Association (MLA)
Zhang, Hai-Gang…[et al.]. A Novel Improved ELM Algorithm for a Real Industrial Application. Mathematical Problems in Engineering No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-501090
American Medical Association (AMA)
Zhang, Hai-Gang& Zhang, Sen& Yin, Yi-Xin. A Novel Improved ELM Algorithm for a Real Industrial Application. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-501090
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-501090