Fuzzy clustering in geospatial analysis

Fuzzy clustering in geospatial analysis

The aim of this work is to explore the method of fuzzy clustering applied for classification of spatial objects or generic geospatial analysis and cluster analysis as a classification of objects by mutual similarities and organize data into groups. Clustering techniques fall into unsupervised method...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Karabegovic, A., Avdagic, Z., Ponjavic, M.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Algorithm design and analysis
Clustering algorithms
Fuzzy logic
Geospatial analysis
Indexes
MATLAB
Spatial databases
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Beschreibung
Zusammenfassung:The aim of this work is to explore the method of fuzzy clustering applied for classification of spatial objects or generic geospatial analysis and cluster analysis as a classification of objects by mutual similarities and organize data into groups. Clustering techniques fall into unsupervised methods, meaning that they do not use predefined class identifiers. The biggest potential of clustering is in recognizing the basic data structures, not only for classification and identification of samples, but also the reduction of models and optimization.