Autosoft Journal

Online Manuscript Access

Research on the Learning Method Based on PCA-ELM



The Single-hidden Layer Feed-forward Neural Network has been widely applied in the fields such as pattern recognition, automatic control and data mining. However, the speed of the traditional learning method, since it is far from enough to satisfy the actual demand has become the main bottleneck, which restricts its development. As one of the new learning methods, the extreme learning machine (ELM) has its own remarkable characteristics, but the fact that ELM is based on the Empirical Risk Minimization may lead to over fitting. In addition, ELM does not consider the weight of error, so its performance will be severely affected when there are outliers in data integration. To solve the above problems, this paper referred to the two algorithms including PCA (Principal Component Analysis) and ELM, and put forward a learning method and prediction model, which combined PCA and ELM. From the results of simulation analysis, as combining advantages of PCA and ELM algorithms, the network structure can be simplified to improve the learning ability and its prediction precision.



Total Pages: 6
Pages: 637-642


Manuscript ViewPdf Subscription required to access this document

Obtain access this manuscript in one of the following ways

Already subscribed?

Need information on obtaining a subscription? Personal and institutional subscriptions are available.

Already an author? Have access via email address?


Volume: 23
Issue: 4
Year: 2017

Cite this document


Chen H.X. Computer Engineering and Application

DENG, Wan-Yu et al. "Research on Extreme Learning of Neural Networks." Chinese Journal of Computers 33.2 (2010): 279-287. Crossref. Web.

Han K. Journal of Shandong University: Engineering science

Horata, Punyaphol, Sirapat Chiewchanwattana, and Khamron Sunat. "Robust Extreme Learning Machine." Neurocomputing 102 (2013): 31-44. Crossref. Web.

Huang, Guang-Bin, and Lei Chen. "Convex Incremental Extreme Learning Machine." Neurocomputing 70.16-18 (2007): 3056-3062. Crossref. Web.

Huang, Guang-Bin, and Lei Chen. "Enhanced Random Search Based Incremental Extreme Learning Machine." Neurocomputing 71.16-18 (2008): 3460-3468. Crossref. Web.

Huang, Guang-Bin, Qin-Yu Zhu, and Chee-Kheong Siew. "Extreme Learning Machine: Theory and Applications." Neurocomputing 70.1-3 (2006): 489-501. Crossref. Web.

Huang, Guang-Bin, Qin-Yu Zhu, and Chee-Kheong Siew. "Extreme Learning Machine: Theory and Applications." Neurocomputing 70.1-3 (2006): 489-501. Crossref. Web.

Huang, Guang-Bin, Xiaojian Ding, and Hongming Zhou. "Optimization Method Based Extreme Learning Machine for Classification." Neurocomputing 74.1-3 (2010): 155-163. Crossref. Web.

Guang-Bin Huang et al. "Extreme Learning Machine for Regression and Multiclass Classification." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 42.2 (2012): 513-529. Crossref. Web.

Li B. Journal of Shangdong University (Natural Science)

Lin J. Computer Simulation

Liu, X.F. (2012a). Grounding grids fault diagnosis based on DCA and PCA-BP neural network . Thesis of Hunan Institute of Science and Technology.

Liu, X.F. (2012b). Fault diagnosis of the grounding networks based on the fame component analysis and the BP neural networks . Unpublished doctoral dissertation, Hunan University, Changsha, China.

Ma X.P. Industry and Mine Automation

Huang, Tingwen et al., eds. "Neural Information Processing." Lecture Notes in Computer Science (2012): n. pag. Crossref. Web.

Wang, X.Y. (2009). The diagnosis technology of the induction motor fault based on BP neural networks . Unpublished doctoral dissertation, Guilin University of Technology, Guilin, China.

Wang H.L. Journal of Harbin institute of Technology University

Wang, Yuguang, Feilong Cao, and Yubo Yuan. "A Study on Effectiveness of Extreme Learning Machine." Neurocomputing 74.16 (2011): 2483-2490. Crossref. Web.

Xiao D. Control Theory & Application

Yadav R.K. International Journal of Artificial Intelligence and Knowledge Discovery

Yang J. Jisuanji Gongcheng yu Yingyong (Computer Engineering and Applications)

Yoan Miche et al. "OP-ELM: Optimally Pruned Extreme Learning Machine." IEEE Transactions on Neural Networks 21.1 (2010): 158-162. Crossref. Web.

Zhu X.Y. SPSS multivariate statistical analysis method and application

Zong, Weiwei, Guang-Bin Huang, and Yiqiang Chen. "Weighted Extreme Learning Machine for Imbalance Learning." Neurocomputing 101 (2013): 229-242. Crossref. Web.


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."

Journal: 1995-Present


TSI Press
18015 Bullis Hill
San Antonio, TX 78258 USA
PH: 210 479 1022
FAX: 210 479 1048