On Cluster Analysis Based on Fuzzy Relations Between Spatial Data

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.

• Type: Conference
• Year: 2007
• Where: EUSFLAT
• Authors: Efendi N. Nasibov, Gözde Ulutagay
• Keywords: EUSFLAT 2007, Fuzzy Logic, Fuzzy Sets Theory, Neighborhood Analysis, Neighborhood Relations