Comparative Analysis of Regression and Neural Network Models for Wind Power
Abstract
This paper compares regression and neural network models for prediction of wind turbine power. The two techniques are first compared theoretically. Then, parameter estimates for the regression model and training of the neural network are completed and the performances of the two models are compared with wind farm data. The regression model is function dependent but the neural network model obtains its prediction through learning. For most cases, the neural network outperforms regression.
Recommended Citation
S. Li et al., "Comparative Analysis of Regression and Neural Network Models for Wind Power," Intelligent Engineering Systems Through Artificial Neural Networks, vol. 8, pp. 675 - 681, American Society of Mechanical Engineers (ASME), Jan 1998.
Meeting Name
Artificial Neural Networks in Engineering Conference (ANNIE 1998) (1998: Nov. 1-4, St. Louis, MO)
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
791800822
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 1998 American Society of Mechanical Engineers (ASME), All rights reserved.
Publication Date
01 Jan 1998
