Wind energy prediction and monitoring with neural computation
Author:
Publisher
Elsevier BV
Subject
Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications
Reference41 articles.
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3. O. Kramer, T. Hein, Monitoring of multivariate wind resources with self-organizing maps and slow feature analysis, in: IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG), IEEE Press, Paris, 2011.
4. D. Lew, M. Milligan, G. Jordan, L. Freeman, N. Miller, K. Clark, R. Piwko, How do wind and solar power affect grid operations: the western wind and solar integration study, in: The Eighth International Workshop on Large Scale Integration of Wind Power and on Transmission Networks for Offshore Wind Farms, 2009.
5. C.W. Potter, D. Lew, J. McCaa, S. Cheng, S. Eichelberger, E. Grimit, Creating the dataset for the western wind and solar integration study (USA), in: The Seventh International Workshop on Large Scale Integration of Wind Power and on Transmission Networks for Offshore Wind Farms, 2008.
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