An Adaptive neuro-Fuzzy Inference System for Sea Level Prediction considering tide-Generating Forces and oceanic thermal Expansion
نویسندگان
چکیده
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 Chang and Lin (2006) that considers the tide-generating forces only. 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.
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