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  1. University of Computer Studies, Yangon
  2. Conferences

Maximum Sustained Wind Prediction of Storm Surge in Bay of Bengal

http://hdl.handle.net/20.500.12678/0000004796
http://hdl.handle.net/20.500.12678/0000004796
0e404e15-cc66-4598-a4a9-f67c16aa16ee
005c0dc0-1672-4b08-89c8-74fb5978bef6
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proceeding_total-pages-95-99.pdf proceeding_total-pages-95-99.pdf (3340 Kb)
Publication type
Article
Upload type
Publication
Title
Title Maximum Sustained Wind Prediction of Storm Surge in Bay of Bengal
Language en
Publication date 2017-02-16
Authors
Tun, A Me
Khine, May Aye
Description
Most of the countries around the Bay ofBengal are threatened by storm surges associatedwith severe tropical cyclones. The destruction alongthe coastal regions of India, Bangladesh, andMyanmar are serious due to the storm surge. Tomitigate the impacts of tropical storm, the predictionof storm surge need to be accurate. Traditionalprocess-based numerical models have the limitationof high computational demands to make timelyforecast and deterministic numerical models arestrongly dependent on accurate meteorological inputto predict storm surge. In this work, a Multilayerperceptron (MLP) and a Radial Basic FunctionNetwork (RBFN) used to predict the maximumsustained wind speed in knots (VMAX) of storm incoastal areas of Bay of Bengal. The ANN networkmodel provides fast, real-time storm surge estimatesat Bay of Bengal. Simulated and historical storm dataare collected for model training and testing,respectively. North India Ocean Best Track Datafrom Joint Typhoon Warning Center (JTWC) used toperform experiments. The result of MLP is predictedVMAX value closer than in RBFN prediction.
Keywords
Artificial Neural Network, storm surge, JTWC
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/691
Journal articles
Fifteenth International Conference on Computer Applications(ICCA 2017)
Conference papers
Books/reports/chapters
Thesis/dissertations
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