An Adaptive Neuro-Fuzzy Inference System for Sea Level Prediction Considering Tide-Generating Forces and Oceanic Thermal Expansion

The paper presents an adaptive neuro fuzzy inference system for predicting sea level considering tide-generating forces and oceanic thermal expansion assuming a model of sea level dependence on sea surface temperature. The proposed model named TGFT-FN (tide-Generating Forces considering sea surface temperature and Fuzzy neuro-network system) is applied to predict tides at five tide gauge sites located in Taiwan and has the root mean square of error of about 7.3 -15.0 cm. The capability of TGFT-FN model is superior in sea level prediction than the previous TGF-NN model developed by The TGFT-FN model is employed to train and predict the sea level of Hua-Lien station, and is also appropriate for the same prediction at the tide gauge sites next to Hua-Lien station.