Simulation of Dengue Outbreak Prediction

Neural Network Model (NNM), Hidden Markov Model (HMM) and Regression Model (RM) are developed to predict the spread of dengue outbreak in Malaysia. The case study covered dengue cases data from Selangor, which include seven mukims and eight administrative districts in year of 2004 and 2005. Specific...

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Main Authors: Husin, Nor Azura, Salim, Naomie, Ahmad, Ab. Rahman
Format: Conference or Workshop Item
Language:English
Published: 2006
Subjects:
Online Access:http://eprints.utm.my/3369/1/Simulation_of_Dengue_Outbreak_Prediction.pdf
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author Husin, Nor Azura
Salim, Naomie
Ahmad, Ab. Rahman
author_facet Husin, Nor Azura
Salim, Naomie
Ahmad, Ab. Rahman
author_sort Husin, Nor Azura
collection ePrints
description Neural Network Model (NNM), Hidden Markov Model (HMM) and Regression Model (RM) are developed to predict the spread of dengue outbreak in Malaysia. The case study covered dengue cases data from Selangor, which include seven mukims and eight administrative districts in year of 2004 and 2005. Specific criteria concerned are location, time (weeks) and intensity of dengue cases. Critical discussion of some previous studies upon the performance of each approach reveals that NNM has several advantages over the two other models in prediction although some limitations are observed and this indicated that NNM might have the better predict of dengue outbreak. However, these models will be further studied by measuring their Root Mean Square Error (RMSE) to identify the best prediction model.
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spelling utm.eprints-33692017-08-27T00:36:20Z http://eprints.utm.my/3369/ Simulation of Dengue Outbreak Prediction Husin, Nor Azura Salim, Naomie Ahmad, Ab. Rahman H Social Sciences (General) QA75 Electronic computers. Computer science Neural Network Model (NNM), Hidden Markov Model (HMM) and Regression Model (RM) are developed to predict the spread of dengue outbreak in Malaysia. The case study covered dengue cases data from Selangor, which include seven mukims and eight administrative districts in year of 2004 and 2005. Specific criteria concerned are location, time (weeks) and intensity of dengue cases. Critical discussion of some previous studies upon the performance of each approach reveals that NNM has several advantages over the two other models in prediction although some limitations are observed and this indicated that NNM might have the better predict of dengue outbreak. However, these models will be further studied by measuring their Root Mean Square Error (RMSE) to identify the best prediction model. 2006-05 Conference or Workshop Item NonPeerReviewed application/pdf en http://eprints.utm.my/3369/1/Simulation_of_Dengue_Outbreak_Prediction.pdf Husin, Nor Azura and Salim, Naomie and Ahmad, Ab. Rahman (2006) Simulation of Dengue Outbreak Prediction. In: Postgraduate Annual Research Seminar 2006 (PARS 2006), 24 - 25 Mei 2006, Postgraduate Studies Department FSKSM, UTM Skudai.
spellingShingle H Social Sciences (General)
QA75 Electronic computers. Computer science
Husin, Nor Azura
Salim, Naomie
Ahmad, Ab. Rahman
Simulation of Dengue Outbreak Prediction
title Simulation of Dengue Outbreak Prediction
title_full Simulation of Dengue Outbreak Prediction
title_fullStr Simulation of Dengue Outbreak Prediction
title_full_unstemmed Simulation of Dengue Outbreak Prediction
title_short Simulation of Dengue Outbreak Prediction
title_sort simulation of dengue outbreak prediction
topic H Social Sciences (General)
QA75 Electronic computers. Computer science
url http://eprints.utm.my/3369/1/Simulation_of_Dengue_Outbreak_Prediction.pdf
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