Based on GIS Spatial Clustering Algorithm Research

Abstract:

Facing the particularity of the current limitations and spatial clustering clustering methods, the objective function from concept clustering starting to GIS spatial data management and spatial analysis for technical support, explores the space between the sample direct access to the distance calculated distance and indirect reach up costs. K samples randomly selected as the cluster center, with space for the sample to reach the center of each cluster sample is divided according to the distance, the sum of the spatial clustering center of the sample to reach its cost objective function for clustering, introduction of genetic algorithm, a spatial clustering algorithm based on GIS. Finally, the algorithm is tested by examples.

• Periodical: Advanced Materials Research (Volumes 971-973)
• Pages: 1565-1568
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.971-973.1565
• Online since: June 2014
• Authors: Zhi Yong Wang*
• Keywords: Clustering Algorithm, Data Mining (DM), Genetic Algorithm (GA), Geographic Information System (GIS)

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