Comparative analysis of regression and neural network models for wind power

Shuhui Li, Edgar O'Hair, Michael G. Giesselmann, Don C. Wunsch

Research output: Contribution to journalReview article

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.

Original languageEnglish
Pages (from-to)675-681
Number of pages7
JournalIntelligent Engineering Systems Through Artificial Neural Networks
Volume1998
StatePublished - 1998

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