Enhancing tidal prediction accuracy in a deterministic model using chaos theory

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Title Enhancing tidal prediction accuracy in a deterministic model using chaos theory
Author Sannasiraj, S.A.; Zhang, Hong; Babovic, Vladan; Chan, Eng Soon
Journal Name Advances in Water Resources
Editor Casey T Miller, D.A. Barry, Marc Parlange
Year Published 2004
Place of publication United Kingdom
Publisher Elsevier Science
Abstract The classical deterministic approach to tidal prediction is based on barotropic or baroclinic models with prescribed boundary conditions from a global model or measurements. The prediction by the deterministic model is limited by the precision of the prescribed initial and boundary conditions. Improvement to the knowledge of model formulation would only marginally increase the prediction accuracy without the correct driving forces. This study describes an improvement in the forecasting capability of the tidal model by combining the best of a deterministic model and a stochastic model. The latter is overlaid on the numerical model predictions to improve the forecast accuracy. The tidal prediction is carried out using a three-dimensional baroclinic model and, error correction is instigated using a stochastic model based on a local linear approximation. Embedding theorem based on the time lagged embedded vectors is the basis for the stochastic model. The combined model could achieve an efficiency of 80% for 1 day tidal forecast and 73% for a 7 day tidal forecast as compared to the deterministic model estimation.
Peer Reviewed Yes
Published Yes
Publisher URI http://www.elsevier.com/wps/find/journaldescription.cws_home/422913/description#description
Alternative URI http://dx.doi.org/10.1016/j.advwatres.2004.03.006
Volume 27
Page from 761
Page to 772
ISSN 0309-1708
Date Accessioned 2004-09-20
Language en_AU
Faculty Faculty of Engineering and Information Technology
Subject PRE2009-Neural Networks, Genetic Alogrithms and Fuzzy Logic; PRE2009-Ocean Engineering
URI http://hdl.handle.net/10072/5173
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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