A Proposed Algorithms for Tidal in-Stream Speed Model
American Journal of Energy Engineering
Volume 1, Issue 1, March 2013, Pages: 1-10
Received: Feb. 8, 2013; Published: Mar. 10, 2013
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Authors
Hamed H. H. Aly, Department of Electrical and Computer Engineering, Dalhousie University, Halifax, Nova Scotia, Canada, B3H 4R2
M. E. El-Hawary, Department of Electrical and Computer Engineering, Dalhousie University, Halifax, Nova Scotia, Canada, B3H 4R2
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Abstract
In this paper we propose four models for tidal current speed and direction magnitude forecasting model. The first model is a Fourier series model based on the least squares method (FLSM), the second model is an artificial neural network (ANN), the third model is a hybrid of FLSM and ANN and the fourth model is a hybrid of ANN and FLSM for monthly forecasting of tidal current speed. These proposed models are ranked in order depending on their performance. These models are validated by using another set of data (tidal current direction). The proposed hybrid model of FLSM and ANN is highly accurate and outperforms. This study was done using data collected from the Bay of Fundy in 2008.
Keywords
Power System Modeling, Tidal Currents, Forecasting, ANN, Fourier Series Based On Least Squares
To cite this article
Hamed H. H. Aly, M. E. El-Hawary, A Proposed Algorithms for Tidal in-Stream Speed Model, American Journal of Energy Engineering. Vol. 1, No. 1, 2013, pp. 1-10. doi: 10.11648/j.ajee.20130101.11
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