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Circular and Cylindrical Hotspots Detection for Spatial and Spatio-temporal Data

Developments in the field of information technology are opening ways to automate many real-life applications by analyzing and solving the problems in more effective way. These real-life applications often required to explore/analyze huge demographic data of social relevance, viz. demographic details of population, crime, education, disease, etc. Many times, highly sensitive demographic areas/data are needed for various decision-making processes in the geo-located based activities. Identification of hotspot is one of such problems, where the highly concentrated regions (for different activities in the demographic area) are needed to be identified. Recently researchers have come out with their proposals to find out many types of hotspots, viz. circular shaped, ring shaped, etc. for various spatial data. In this paper, we propose differential evolution based approach to find out circular and cylindrical shaped hotspots for spatial and spatio-temporal data respectively. We modified the differential evolution approach to propose our method and find out the hotspot over the crime, employment, and literacy records of India from 2001 to 2012.