Back-Propagation Neural Network in Tidal-Level Forecasting
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VIEW THE REPLYPublication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 125, Issue 4
Abstract
Reliability of tidal-level forecasting is essential for structure installation and human activities in the marine environment. This paper reports an application of the artificial neural network with back-propagation procedures for accurate forecast of tidal-level variations. Unlike the conventional harmonic analysis, this neural network model forecasts the time series of tidal levels directly using a learning process based on a set of previous data. Two sets of field data with diurnal and semidiurnal tide, respectively, were used to test the performance of the neural network model. Results indicate that the hourly tidal levels over a long duration can be efficiently predicted using only a very short-term hourly tidal record.
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Published In
Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 125 • Issue 4 • July 1999
Pages: 195 - 202
History
Received: Mar 17, 1998
Published online: Jul 1, 1999
Published in print: Jul 1999
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