Lee, T.L.  , C.P. Tsai  , R.J. Shieh  , 
    Applied the Back-propagation Neural Network to Predict Long-term Tidal Level,
    Asian Journal of Information Technology,
    Volume 5,Issue 4,
    2006,
    Pages 396-401,
    ISSN 1682-3915,
    ajit.2006.396.401,
    (https://makhillpublications.co/view-article.php?doi=ajit.2006.396.401)
    Abstract: Prediction of tide levels is rather an important task in determining constructions and human activities
in coastal and oceanic area. Accurate predictions of tide levels could not be obtained without a large length
of tide measurements by conventional methods. The Back-Propagation Neural Network (PBN) was applied to
predict long term semi-diurnal tidal level. Based on the model, the different tide types for other two field data,
referred as the diurnal and mixed types, are further to test the performance of PBN model. The results also
present that one-year tidal level forecasting can be satisfactorily achieved using a half-month length of
observed data for these two tide types.
    Keywords: Back-propagation neural network;long term;prediction