ON cluster analysis based on fuzzy relations between spatial data
Conference paper > Full Text · 2007
Authors: Efendi Nasibov, Gözde ULUTAGAY
5th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2007, , International, Invitee, Full Text, 2007-2007, vol 2, pp 59-62
Summary
Methods like DBSCAN are widely used in the analysis of spatial data. These methods are based on the neighborhood relations which use distance between points. However, these neighborhood relations consider to have at least a certain number of neighbors within a definite boundary. In this proposed work such a neighborhood analysis is done by using the benefits of fuzzy sets theory. Usage of fuzzy logic gives more sensitive and realistic results. In this paper, Fuzzy Joint Points (FJP) based on this theory is handled and some theoretical properties used in neighborhood analysis are investigated.