Neighborhood Rough Set Based Similarity Measurement Ofsubzones Affected by West Nile Virus

There are many methods that can be used to compute the geographic similarity between regions represented through areas in a two dimensional space. However, it is the rough set based membership function that allows an estimate of the similarity between a subzone formed by the data. The major objective behind this paper is to measure the similarity of GIS subzones on a discrete dataset. This has a varied number of applications not only in GIS and epidemiology but also in clusters analysis and artificial intelligence.

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