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Computational Intelligence and Neuroscience
Volume 2017, Article ID 7273017, 14 pages
https://doi.org/10.1155/2017/7273017
Research Article

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

1School of Physics and Electrical Engineering, Anyang Normal University, Anyang 455000, China
2College of Electronic Information and Automation, Tianjin University of Science & Technology, Tianjin 300222, China

Correspondence should be addressed to Xiang-ming Gao; moc.361@oagcbca

Received 20 March 2017; Revised 14 June 2017; Accepted 27 June 2017; Published 22 August 2017

Academic Editor: José Alfredo Hernández-Pérez

Copyright © 2017 Xiang-ming Gao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Xiang-ming Gao, Shi-feng Yang, and San-bo Pan, “Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction,” Computational Intelligence and Neuroscience, vol. 2017, Article ID 7273017, 14 pages, 2017. https://doi.org/10.1155/2017/7273017.