A Proposed ANN and FLSM Hybrid Model for Tidal Current Magnitude and Direction Forecasting

Author

Aly, Hamed H. H. ; El-Hawary, M.E.

Author_Institution

Dept. of Electr. & Comput. Eng., Dalhousie Univ., Halifax, NS, Canada

Volume

39

Issue

1

fYear

2014

fDate

Jan. 2014

Firstpage

26

Lastpage

31

Abstract

The paper proposes a hybrid model of an artificial neural network (ANN) and Fourier series model based on the least squares method (FLSM) for monthly forecasting of tidal current magnitude and direction. The proposed hybrid model is highly accurate and outperforms either of the ANN or the FLSM applied alone. This study was done using data collected from the Bay of Fundy, NS, Canada, in 2008.

Keywords

Fourier series; geophysics computing; least squares approximations; modelling; neural nets; oceanographic regions; oceanographic techniques; tides; AD 2008; ANN-FLSM hybrid model; Canada; Fundy Bay; artificial neural network; direction forecasting; least squares method based Fourier series model; tidal current direction monthly forecast; tidal current magnitude monthly forecast; Analytical models; Artificial neural networks; Data models; Forecasting; Predictive models; Technological innovation; Training; Artificial neural network (ANN); forecasting; least squares estimation; power system modeling; tidal currents;

fLanguage

English

Journal_Title

Oceanic Engineering, IEEE Journal of

Publisher

ieee

ISSN

0364-9059

Type

jour

DOI

10.1109/JOE.2013.2241934

Filename

6480853