Abstract
The knowledge of ocean waves is an essential prerequisite for almost all activities in ocean. Traditional methods have disadvantages of excessive data requirement, time consumption and are tedious to carry out. ANN is being widely applied in coastal engineering field since last two decades in variety of time series forecasting. Study has been carried out to predict waves using FFBP and NARX networks. Wave data obtained from INCOIS is made use in the present study. Effect of network architecture on the performance of the model has been studied. It was found that for time series prediction NARX network outperforms FFBP.
Highlights
Accurate forecasting of wave characteristics is important for many coastal and marine activities
The curves developed by Sverdrup and Munk in 1947 and Pierson, Neumann and James in 1955 (PNJ) were used for wave forecasting
The basic difference between the two is that, in feed forward networks the information is passed from one layer to the other in a forward manner till the output is obtained in the output layer
Summary
Accurate forecasting of wave characteristics is important for many coastal and marine activities. Different methods have been developed for this purpose. There are many empirical formulae for wave growth which have been derived from large visually observed data sets. The curves developed by Sverdrup and Munk in 1947 and Pierson, Neumann and James in 1955 (PNJ) were used for wave forecasting. These two number of visual observations by graphical methods using known parameters of wave characteristics. Its major disadvantage is the time necessary to make the computations and it requiring large information about oceanographic and meteorological data
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