NDLI: Typhoon Surge Forecasting with Artificial Back-propagation Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Jan, C.D. Tseng, C.M. Wang, J.S. Wang, C.M.
Copyright Year	2006
Description	Author affiliation: Nat. Cheng Kung Univ., Tainan (Jan, C.D.)
Abstract	A typhoon-surge forecasting model was developed with the application of the back-propagation neural network (BPN) in the present paper. This artificial neural network model forecasts the hourly time series of typhoon surge variation based on a set of input data including typhoon's characteristics, local meteorological conditions and typhoon surges at a considered tidal station. For selecting a better forecasting model, four models (Models A, B, C, and D) were tested and compared under the different composition of input factors. A general evaluation index that is a composition of four performance indexes was proposed to evaluate the model's overall performance. Tested results show that Model D composing 18 input factors has best performance among the four models, The Model D was then applied to typhoon-surge forecasting at Cheng-kung Tidal Station in south-eastern coast of Taiwan and at Tung-shih Tidal Station in the coast of south-western Taiwan. Results show that the application of Model D in typhoon-surge forecasting at Cheng-kung Tidal Station has better performance than that at Tung-shih Tidal Station.
Starting Page	1
Ending Page	7
File Size	6911615
Page Count	7
File Format	PDF
ISBN	9781424401376
DOI	10.1109/OCEANSAP.2006.4393894
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-16
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Typhoons Surges Artificial neural networks Predictive models Weather forecasting Storms Meteorology Sea measurements Tides Rivers
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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