eprintid: 8981
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/89/81
datestamp: 2023-11-09 16:20:55
lastmod: 2023-11-09 16:20:55
status_changed: 2023-11-09 16:13:59
type: conference_item
metadata_visibility: show
creators_name: Mathur, N.
creators_name: Asirvadam, V.S.
creators_name: Dass, S.C.
creators_name: Gill, B.S.
title: Visualization of dengue incidences using expectation maximization (EM) algorithm
ispublished: pub
keywords: Forecasting; Geographic information systems; Maximum principle; Visualization, Centroid models; Controlled process; Dengue; Distribution models; EM algorithms; Expectation-maximization algorithms; K-means; Prediction model, Clustering algorithms
note: cited By 3; Conference of 6th International Conference on Intelligent and Advanced Systems, ICIAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125970
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.
date: 2017
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011964903&doi=10.1109%2fICIAS.2016.7824047&partnerID=40&md5=1a2347b7f3c5484caaf2e644dd258024
id_number: 10.1109/ICIAS.2016.7824047
full_text_status: none
publication: International Conference on Intelligent and Advanced Systems, ICIAS 2016
refereed: TRUE
isbn: 9781509008452
citation:   Mathur, N. and Asirvadam, V.S. and Dass, S.C. and Gill, B.S.  (2017) Visualization of dengue incidences using expectation maximization (EM) algorithm.  In: UNSPECIFIED.