A Novel Spatial Fuzzy Clustering using Delaunay Triangulation for Large Scale GIS Data (NSFCDT) | Zendy

Parthajit Roy | Zendy; Jyotsna Kumar Mandal | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Novel Spatial Fuzzy Clustering using Delaunay Triangulation for Large Scale GIS Data (NSFCDT)

Author(s) -

Parthajit Roy,

Jyotsna Kumar Mandal

Publication year - 2012

Publication title -

procedia technology

Language(s) - English

Resource type - Journals

ISSN - 2212-0173

DOI - 10.1016/j.protcy.2012.10.054

Subject(s) - delaunay triangulation , cluster analysis , data mining , scale (ratio) , bowyer–watson algorithm , spatial analysis , computer science , constrained delaunay triangulation , voronoi diagram , fuzzy clustering , artificial intelligence , geography , mathematics , remote sensing , algorithm , cartography , geometry

This paper proposed a novel fuzzy clustering method on spatial data based on Delaunay Triangulation. Given a set of points in a two dimensional space, the objective is to group the data into several sets. The model uses two passes. In the first pass, the underlying model used a Delaunay Triangulation method for initial spatial clustering. The clustering, in this pass, is done on the notion of proximity of points. The Fuzzy method is applied as a post processing refinement of the clusters in the second pass. The underlying mathematical backbone of the proposed model along with the correctness of the algorithm has also been conformed

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research