Prediction of tides using back-propagation neural networks
Abstract
Prediction of tides is very much essential for human activities and to reduce the construction cost in marine environment. This paper presents an application of the artificial neural network with back-propagation procedures for accurate prediction of tides. This neural network model predicts the time series data of hourly tides directly while using an efficient learning process called quickprop based on a previous set of data. Hourly tidal data measured at Gopalpur port - east coast of India was used for testing the back-propagation neural network model. Results show that the hourly data on tides for even a month can be predicted efficiently with a very high correlation coefficient (=0.9984).
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