NDLI: Prediction of Typhoon Losses in the South-East of China Based on B-P Network

Content Provider	IEEE Xplore Digital Library
Author	Wenbin Sun Shigang Shan Cuicui Zhang Peipei Ge Liangliang Tao
Copyright Year	2010
Abstract	Assessing typhoon losses quickly is the foundation to allocate and deliver relief supplies for helping disastrous people pull through difficulties during the process of typhoon and post-disaster immediately. Therefore, a new method for predicting typhoon losses based on back-propagation neural network is presented by using typhoon characters data, historic typhoon loss data, relative geographical spatial data and population data in this paper. Our approaches start with constructing typhoon losses model based on back-propagation neural network. Then, ascertaining input and output variables of training samples is described. In the end, the experiment is done to test the feasibility of methods approached in this paper by using historic land falling typhoon data during 2005-2007 in China south-east. The result indicates that this model is effective and prediction results are good and receptive.
Starting Page	252
Ending Page	256
File Size	365512
Page Count	5
File Format	PDF
ISBN	9781424484324
DOI	10.1109/AICI.2010.60
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Typhoons Buildings Linear regression Artificial neural networks Prediction Predictive models Back-propagation neural network Mathematical model Equations Typhoon losses
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
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A Genetic Neural Network ensemble prediction model based on Locally Linear Embedding for typhoon intensity

A Nonlinear Artificial Intelligence Ensemble Prediction Model Based on EOF for Typhoon Track

An Neural Network Ensemble approach based on PSO algorithm and LLE for Typhoon Intensity

Typhoon Surge Forecasting with Artificial Back-propagation Neural Networks

Application of improved BP neural network in predicting subsidence of buildings

A rainfall prediction model using artificial neural network

A Genetic-Neural Network Model Based on Multidimensional Scaling for Typhoon Intensity

Studies on typhoon-wave prediction by Artificial Neural Networks at Longdong, Taiwan

A Particle Swarm Optimization-Neural Network Prediction Model for Typhoon Intensity Based on Isometric Mapping Algorithm

Prediction of Typhoon Losses in the South-East of China Based on B-P Network

Similar Documents

A Genetic Neural Network ensemble prediction model based on Locally Linear Embedding for typhoon intensity

A Nonlinear Artificial Intelligence Ensemble Prediction Model Based on EOF for Typhoon Track

An Neural Network Ensemble approach based on PSO algorithm and LLE for Typhoon Intensity

Typhoon Surge Forecasting with Artificial Back-propagation Neural Networks

Application of improved BP neural network in predicting subsidence of buildings

A rainfall prediction model using artificial neural network

A Genetic-Neural Network Model Based on Multidimensional Scaling for Typhoon Intensity

Studies on typhoon-wave prediction by Artificial Neural Networks at Longdong, Taiwan

A Particle Swarm Optimization-Neural Network Prediction Model for Typhoon Intensity Based on Isometric Mapping Algorithm

Prediction of Typhoon Losses in the South-East of China Based on B-P Network