Development of dengue prediction model with neural network

The aim of this project is to develop a system that could predict the Dengue outbreak. This is done by using the prediction variables such as climate and past data. Two approaches will be used to develop the prediction models, which are Artificial Neural Network (ANN) and Generalized Additive Mod...

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Main Author: Cheo, Jia Jun
Format: Final Year Project / Dissertation / Thesis
Published: 2022
Subjects:
Online Access:http://eprints.utar.edu.my/4726/1/fyp_IA_2022_CJJ.pdf
http://eprints.utar.edu.my/4726/
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author Cheo, Jia Jun
author_facet Cheo, Jia Jun
author_sort Cheo, Jia Jun
building UTAR Library
collection Institutional Repository
content_provider Universiti Tunku Abdul Rahman
content_source UTAR Institutional Repository
continent Asia
country Malaysia
description The aim of this project is to develop a system that could predict the Dengue outbreak. This is done by using the prediction variables such as climate and past data. Two approaches will be used to develop the prediction models, which are Artificial Neural Network (ANN) and Generalized Additive Models (GAMs). Then, the prediction accuracy of the models will be compared. All methods can handle real life input to simulate the situation of the area where we want to predict outbreak of Dengue. It is believed that the accurate prediction of dengue outbreakcan reduce the dengue case and prevent the dengue outbreak in Malaysia.
format Final Year Project / Dissertation / Thesis
id my-utar-eprints.4726
institution Universiti Tunku Abdul Rahman
publishDate 2022
record_format eprints
spelling my-utar-eprints.47262023-01-10T09:00:34Z Development of dengue prediction model with neural network Cheo, Jia Jun T Technology (General) The aim of this project is to develop a system that could predict the Dengue outbreak. This is done by using the prediction variables such as climate and past data. Two approaches will be used to develop the prediction models, which are Artificial Neural Network (ANN) and Generalized Additive Models (GAMs). Then, the prediction accuracy of the models will be compared. All methods can handle real life input to simulate the situation of the area where we want to predict outbreak of Dengue. It is believed that the accurate prediction of dengue outbreakcan reduce the dengue case and prevent the dengue outbreak in Malaysia. 2022-05 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4726/1/fyp_IA_2022_CJJ.pdf Cheo, Jia Jun (2022) Development of dengue prediction model with neural network. Final Year Project, UTAR. http://eprints.utar.edu.my/4726/
spellingShingle T Technology (General)
Cheo, Jia Jun
Development of dengue prediction model with neural network
title Development of dengue prediction model with neural network
title_full Development of dengue prediction model with neural network
title_fullStr Development of dengue prediction model with neural network
title_full_unstemmed Development of dengue prediction model with neural network
title_short Development of dengue prediction model with neural network
title_sort development of dengue prediction model with neural network
topic T Technology (General)
url http://eprints.utar.edu.my/4726/1/fyp_IA_2022_CJJ.pdf
http://eprints.utar.edu.my/4726/
url_provider http://eprints.utar.edu.my