Recognition of dengue disease patterns using artificial neural networks

This research aimed at the recognition of the patterns for dengue disease patterns using Artificial Neural Networks (ANN’s). Real data was provided by Singaporean National Environment Agency (NEA), for academic purposes only. Obtained data was used to model the behavior of dengue cases based on...

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Main Authors: Cetiner, Beytullah Gultekin, Sari, Murat, Aburas, Hani M.
Format: Proceeding Paper
Language:English
Published: 2009
Subjects:
Online Access:http://irep.iium.edu.my/13260/
http://irep.iium.edu.my/13260/1/Recognition_of_dengue_disease_patterns_using_artificial_neural_networks.pdf
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author Cetiner, Beytullah Gultekin
Sari, Murat
Aburas, Hani M.
author_facet Cetiner, Beytullah Gultekin
Sari, Murat
Aburas, Hani M.
author_sort Cetiner, Beytullah Gultekin
building IIUM Repository
collection Online Access
description This research aimed at the recognition of the patterns for dengue disease patterns using Artificial Neural Networks (ANN’s). Real data was provided by Singaporean National Environment Agency (NEA), for academic purposes only. Obtained data was used to model the behavior of dengue cases based on the physical parameters of mean temperature, mean relative humidity and total rainfall. The set of data recorded weekly consists of dengue reported confirmed cases together with three aforementioned parameters and for a six-year period, January 2001 to April 2007.
first_indexed 2025-11-14T14:47:39Z
format Proceeding Paper
id iium-13260
institution International Islamic University Malaysia
institution_category Local University
language English
last_indexed 2025-11-14T14:47:39Z
publishDate 2009
recordtype eprints
repository_type Digital Repository
spelling iium-132602011-12-27T04:07:49Z http://irep.iium.edu.my/13260/ Recognition of dengue disease patterns using artificial neural networks Cetiner, Beytullah Gultekin Sari, Murat Aburas, Hani M. QR Microbiology This research aimed at the recognition of the patterns for dengue disease patterns using Artificial Neural Networks (ANN’s). Real data was provided by Singaporean National Environment Agency (NEA), for academic purposes only. Obtained data was used to model the behavior of dengue cases based on the physical parameters of mean temperature, mean relative humidity and total rainfall. The set of data recorded weekly consists of dengue reported confirmed cases together with three aforementioned parameters and for a six-year period, January 2001 to April 2007. 2009 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/13260/1/Recognition_of_dengue_disease_patterns_using_artificial_neural_networks.pdf Cetiner, Beytullah Gultekin and Sari, Murat and Aburas, Hani M. (2009) Recognition of dengue disease patterns using artificial neural networks. In: 5th International Advanced Technologies Symposium (IATS'09), 13-15 May, 2009, Karabuk, Turkey.
spellingShingle QR Microbiology
Cetiner, Beytullah Gultekin
Sari, Murat
Aburas, Hani M.
Recognition of dengue disease patterns using artificial neural networks
title Recognition of dengue disease patterns using artificial neural networks
title_full Recognition of dengue disease patterns using artificial neural networks
title_fullStr Recognition of dengue disease patterns using artificial neural networks
title_full_unstemmed Recognition of dengue disease patterns using artificial neural networks
title_short Recognition of dengue disease patterns using artificial neural networks
title_sort recognition of dengue disease patterns using artificial neural networks
topic QR Microbiology
url http://irep.iium.edu.my/13260/
http://irep.iium.edu.my/13260/1/Recognition_of_dengue_disease_patterns_using_artificial_neural_networks.pdf