A proposed algorithms for tidal in-stream speed model

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.

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