%P 227-232
%A N. Mathur
%A V.S. Asirvadam
%A S.C. Dass
%A B.S. Gill
%I Institute of Electrical and Electronics Engineers Inc.
%T Generating vulnerability maps of dengue incidences for Petaling district in Malaysia
%J Proceeding - 2016 IEEE 12th International Colloquium on Signal Processing and its Applications, CSPA 2016
%L scholars6918
%O cited By 3; Conference of 12th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2016 ; Conference Date: 4 March 2016 Through 6 March 2016; Conference Code:122817
%R 10.1109/CSPA.2016.7515836
%D 2016
%X Dengue has been reported as a major cause of morbidity and mortality for the last 40 years worldwide including Malaysia. This work develops and implements visualization and predictive modelling for dengue in Malaysia. The incidences are visualized using Geographical Information System (GIS) which provides information on coordinates (latitude and longitude) based on the occurrence of incidences registered with the Disease Control Division of the Ministry of Health, Malaysia. Clustering is performed on this data using centroid and distribution models that are representatives of K-means and the Expectation Maximization (EM) algorithms, respectively. The results are validated for Petaling district of Selangor and are shown to possess good performance in predicting the dengue incidences. The proposed method is able to localize the incidences which can further be utilized for vector disease control processes. © 2016 IEEE.
%K Algorithms; Disease control; Geographic information systems; Maximum principle; Signal processing, Control process; dengue; Distribution models; EM algorithms; Expectation-maximization algorithms; K-means; Predictive modelling; Vulnerability maps, Clustering algorithms