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Journal of Renewable Energy
Volume 2014 (2014), Article ID 986830, 15 pages
http://dx.doi.org/10.1155/2014/986830
Research Article

Comparison and Optimization of Neural Networks and Network Ensembles for Gap Filling of Wind Energy Data

1Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
2Department of Geography, Ruhr University Bochum, 44780 Bochum, Germany

Received 28 January 2014; Revised 15 April 2014; Accepted 16 April 2014; Published 26 May 2014

Academic Editor: Shuhui Li

Copyright © 2014 Andres Schmidt and Maya Suchaneck. 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

Andres Schmidt and Maya Suchaneck, “Comparison and Optimization of Neural Networks and Network Ensembles for Gap Filling of Wind Energy Data,” Journal of Renewable Energy, vol. 2014, Article ID 986830, 15 pages, 2014. doi:10.1155/2014/986830