DocumentCode
1797957
Title
Estuarine flood modelling using artificial neural networks
Author
Fazel, Seyyed Adel Alavi ; Blumenstein, Michael ; Mirfenderesk, Hamid ; Tomlinson, Rodger
Author_Institution
Sch. of Inf. & Commun. Technol., Griffith Univ. Gold Coast Campus, Gold Coast, QLD, Australia
fYear
2014
fDate
6-11 July 2014
Firstpage
631
Lastpage
637
Abstract
Prediction of water levels at estuaries poses a significant challenge for modelling of floods due to the influence of tidal effects. In this study, a two-stage forecasting system is proposed. In the first stage, the tidal portion of the available records is used to develop a tidal prediction system. The predictions of the first stage are used for flood modelling in the second. Experimental results suggest that the proposed flood modelling approach is advantageous for forecasting flood levels with more than 1 hour lead times.
Keywords
floods; forecasting theory; geophysics computing; neural nets; tides; artificial neural networks; estuarine flood modelling; flood level forecasting; tidal effects; tidal prediction system; two-stage forecasting system; water level prediction; Artificial neural networks; Floods; Forecasting; Mathematical model; Predictive models; Time series analysis; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6627-1
Type
conf
DOI
10.1109/IJCNN.2014.6889704
Filename
6889704
Link To Document