Chaos theory in predicting surge water levels in the North Sea

Abstract

ABSTRACT: The problem of predicting surge water levels is important for ship guidance and navigation. The data collected in the coastal waters of the Netherlands (Hook of Holland) is analysed with an objective of making such prediction. It was found that the correlation between data on surge, temperature, air pressure and wind is not sufficient to rely only on the input-output (connectionist) models like neural networks. It appeared that the surge time series in itself has enough information to make predictions. The applied linear prediction methods including autocorrelation and ARIMA models could not provide sufficient accuracy. Features of chaotic behaviour were identified in surge, and methods of chaos theory were applied. The predictions are quite accurate (RMSE is 3.6 cm for 1 hour, and 6.1 cm for 3 hours). Possible techniques allowing for increase of the prediction accuracy and horizon (wavelet analysis, data mining techniques) were also identified.