Analysis of Mean-shift Algorithm to Detect Hotspots of Dengue Fever Outbreak

Praveen Kumar, Anisha Rani, Ashok Rawat and Seema Rawat

To control irresistible infections, epidemiologic data and helpful clustering methods can be coordinated to decide the potential regions of disease flare-ups dependent on day by day reconnaissance data. In this paper, we present the utilization of Mean-Shift in infection reconnaissance. This calculation depends on a nonparametric clustering which is intended to recognize clusters of discretionary shape. In 2015, Delhi has chronicled its most exceedingly awful episode since 2006 with more than 15000 cases (WHO factsheet, 2016) and along these lines, to lessen the high danger of dengue transmission in Delhi, proactive reconnaissance and mediation measures are required to control the potential flare-ups of dengue. The present examination has been observed to be effective in deciding the hotspot of DF. Silhouette Coefficient, Homogeneity, Completeness, V-Measure, Adjusted Rand Index and Adjusted Mutual Index. Hotspots have been generated.

Volume 11 | Issue 10

Pages: 27-35

DOI: 10.5373/JARDCS/V11I10/20193002