Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package

Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package

Link to publisher's homepage at http://www.myiem.org.my/

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Bibliographic Details
Main Author: Lee, Wei Koon
Other Authors: leewei994@salam.uitm.edu.my
Format: Article
Language:English
Published: The Institution of Engineers, Malaysia 2011
Subjects:
Artificial neural network
Back-propagation
Graphical user interface
Harmonic analysis
Tidal forecast
Tidal hindcast
QuickTIDE
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/13733
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Institution: Universiti Malaysia Perlis
Language: English
id my.unimap-13733
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spelling my.unimap-137332011-09-13T06:17:01Z Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package Lee, Wei Koon leewei994@salam.uitm.edu.my Artificial neural network Back-propagation Graphical user interface Harmonic analysis Tidal forecast Tidal hindcast QuickTIDE Link to publisher's homepage at http://www.myiem.org.my/ A tidal simulation package built on MATLAB neural network toolbox with user-friendly graphical user interface (GUI) is presented. The application, named QuickTIDE, is modeled using a back-propagation neural network (BPN) with single hidden layer and five input constituents. Twenty-one built-in network models trained on one-year hourly tidal observations are able to generate reliable tidal simulation from year 1994 to 2004 corresponding to their respective locations in Malaysia. Further tests on the historical data of station Boston Harbour from year 1930 to 2000 show that good forecast and hindcast can be produced up to 70 years if the number of neuron in the hidden layer and the number of input argument are properly selected. Using 30- day hourly observations, the application is capable of producing satisfactory simulation with average correlation coefficient R in the order of 0.96 from year 1994 to 2004 for station Port Klang. For forecasting and hindcasting from year 1930 to 2000 for station Boston Harbour, R-values average at 0.92 and 0.90 respectively, with better results in the month the training data originates. 2011-09-13T06:17:01Z 2011-09-13T06:17:01Z 2007-06 Article The Journal of the Institution of Engineers, Malaysia, vol. 68(2), 2007, pages 58-64 0126-513X http://myiem.org.my/content/iem_journal_2007-178.aspx http://hdl.handle.net/123456789/13733 en The Institution of Engineers, Malaysia
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Artificial neural network
Back-propagation
Graphical user interface
Harmonic analysis
Tidal forecast
Tidal hindcast
QuickTIDE
spellingShingle Artificial neural network
Back-propagation
Graphical user interface
Harmonic analysis
Tidal forecast
Tidal hindcast
QuickTIDE
Lee, Wei Koon
Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package
description Link to publisher's homepage at http://www.myiem.org.my/
author2 leewei994@salam.uitm.edu.my
author_facet leewei994@salam.uitm.edu.my
Lee, Wei Koon
format Article
author Lee, Wei Koon
author_sort Lee, Wei Koon
title Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package
title_short Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package
title_full Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package
title_fullStr Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package
title_full_unstemmed Long-term tidal forecasting and hindcasting using QuickTIDE tidal simulation package
title_sort long-term tidal forecasting and hindcasting using quicktide tidal simulation package
publisher The Institution of Engineers, Malaysia
publishDate 2011
url http://dspace.unimap.edu.my/xmlui/handle/123456789/13733
_version_ 1643790953013575680

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