Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

Yazarlar: Hüseyin Zahit SELVİ, Burak ÇAĞLAR

Konular:Mühendislik, Ortak Disiplinler

DOI:10.28948/ngumuh.341267

Anahtar Kelimeler:Multivariate mapping,Data mining,Cluster analysis

Özet:    Multivariate mapping is the visual exploration of spatial objects with multiple attributes using a map. More than one attribute can be visually explored and symbolized using numerous statistical classification systems or data reduction techniques. In this sense, clustering analysis methods can be used for multivariate mapping. In this study, among clustering analysis methods, k-means method, k-medoids method and Agglomerative Hierarchical Clustering method were selected. For this purpose, multivariate maps created from traffic accident data of two different years in Turkey were used. The methods were compared using the maps produced with these methods and effectiveness of these maps in risk management and planning were discussed.

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