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Simulation of Dengue Outbreak Prediction

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.

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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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Neural Network, Hidden Markov, Regression, Dengue outbreak prediction.
Subjects:H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:3369
Deposited By: Mrs Rozilawati Dollah @ Md Zain
Deposited On:24 May 2007 00:47
Last Modified:27 Aug 2017 00:36

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