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High performance computing for spatial scan statistics

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dc.contributor.author Dahiya, Lakshay
dc.contributor.author Singh, Chaudhary Guroosh Gabriel
dc.contributor.author Gunturi, Venkata M. Viswanath (Advisor)
dc.date.accessioned 2018-09-24T10:19:22Z
dc.date.available 2018-09-24T10:19:22Z
dc.date.issued 2018-08-13
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/662
dc.description.abstract With the advent of mobile phones and wearable technology, there has been a sudden increase in the amount of geo-located data available to us. One of the basic forms of pattern recognition is the identification of hotspots. These can range from crime hotspots to disease-prone areas to identifying dense forest areas. In this report we implement a parallel version of Significant Linear Hotspot Discovery algorithm by using Neighbor Node filter optimization for detecting linear hotspots, a follow up on our previous work which was on circular hotspots. en_US
dc.language.iso en_US en_US
dc.publisher IIIT-Delhi en_US
dc.subject Spatial Science en_US
dc.subject High Performance Computing en_US
dc.subject Parallel Architecture en_US
dc.subject Hotspot Detection en_US
dc.subject Density Ratio en_US
dc.title High performance computing for spatial scan statistics en_US
dc.type Other en_US


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