Author(s): Prashanth Janardhan, Harish Narayan, Sukomal Mandal
Linked Author(s): Prashanth Janardhan
Keywords: Tidal current, harmonic analysis, tidal constituents, artificial neural network
Abstract: Tides are the rise and fall of water level caused by gravitational forces exerted by the sun, moon and earth. Understanding sea level variation and its impact on currents is very important especially in coastal regions. Traditional methods such as harmonic analysis, least mean squares method, and hydrodynamic models have disadvantages in that they require excessive data, are time consuming, and are tedious to carry out. Artificial Neural Network (ANN) has been widely applied in the coastal engineering field in the last two decades for solving various problems related to time series forecasting of waves and tides; predicting sea-bed liquefaction and scour depth; and estimating design parameters of coastal engineering structures. In the present study, an attempt was made to predict the tides in the area off Mithividi which is north of Alang ship breaking yard, Gujarat, west coast of India using tidal harmonic analysis and ANN. Predictions were carried out for various durations using the daily and weekly data sets. The harmonic analysis predicted mixed semidurinal dominant tide which is the same as the field data. The results are compared and it is observed that ANN can be a good alternative tool for tidal prediction. Results obtained are encouraging with �r� value greater than 0. 94
Year: 2017