Logo

Visualization of dengue incidences using expectation maximization (EM) algorithm

Mathur, N. and Asirvadam, V.S. and Dass, S.C. and Gill, B.S. (2017) Visualization of dengue incidences using expectation maximization (EM) algorithm. International Conference on Intelligent and Advanced Systems, ICIAS 2016 .

Full text not available from this repository.

Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The aim of this study was to use the geographical information system (GIS) to visualize the dengue incidences on a weekly basis in Selangor, Malaysia. Along with the prediction modeling on data using centroid model and distribution model based on K-means and Expectation Maximization (EM) algorithms respectively. The results show that weekly hotspot were mainly concentrated in the central part of Petaling district of Selangor. R-GIS(R software) and clustering algorithm were used for year 2014 with several weeks to develop the relation between the visualization and prediction of reported incidences. The results are validated for a small region (Petaling district of Selangor state) in Malaysia and they showed vulnerability hotspot in visualizing the dengue incidences. Thus, the proposed method is able to localize the nature of dengue incidence which can further be utilized for vector disease controlled process. © 2016 IEEE.

Item Type:Article
Impact Factor:cited By 0
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
ID Code:20234
Deposited By: Ahmad Suhairi
Deposited On:22 Apr 2018 14:46
Last Modified:22 Apr 2018 14:46

Repository Staff Only: item control page