Hybrid harmonic analysis and wavelet network model for sea water level prediction

Abstract

Accurate sea water level prediction is required for safe marine navigation in shallow waters as well as for other marine operations. Traditionally, tide prediction is commonly carried out using only the harmonic analysis (HA-only) model or only a wavelet network (WN-only) model. The harmonic analysis method is the most reliable model for long term sea water level prediction when long data records are available and in contrast the wavelet network method is the most reliable model used for short term sea water level prediction when short data records are available. This paper developed a hybrid harmonic analysis and wavelet network (HA-and-WN) model for accurate sea water level prediction. To validate the hybrid HA-and-WN model, sea water level data from four tide gauges are employed to investigate the performance of the developed hybrid model. It is shown that the majority of error values at 95% confidence level fall within ±14.77cm, ±2.65cm and ±2.08cm range in average with maximum error of 36.84cm, 9.21cm and 7.00cm in average for HA-only model, WN-only model and hybrid HA-and-WN model, respectively. Also, it is found that the root-mean-squared (RMS) errors are about 9.75cm, 1.85cm and 1.49cm for HA-only, WN-only and hybrid HA-and-WN models, respectively, based on the overall performance from the four tide gauges under implementation. Therefore, it is concluded that the developed hybrid HA-and-WN model is superior to the HA-only model by about 85% and outperforms the WN-only model by about 20%, based on the overall RMS errors.