ÇOK DEĞİŞKENLİ HARİTALAMA İÇİN KÜMELEME YÖNTEMLERİNİN KULLANILMASI

Year 2017, Volume: 6 Issue: 2, 415 - 429, 31.07.2017

Hüseyin Zahit Selvi , Burak Çağlar

https://doi.org/10.28948/ngumuh.341267

Cited By: 7

Abstract

   Çok değişkenli haritalama mekânsal objelere ait birden çok özelliğin
harita kullanılarak görsel sunumudur. Çeşitli veri hazırlama ve istatistiksel
sınıflandırma teknikleri kullanılarak mekânsal objelere ait birden çok özellik
görsel olarak incelenebilir ve kartografik işaretlerle gösterilebilir. Bu
kapsamda kümeleme analizi yöntemleri de çok değişkenli haritalama için
kullanılabilir. Bu çalışmada kümeleme analiz yöntemlerinden k-ortalama yöntemi,
k-temsilci yöntemi ve Birleştirici Hiyerarşik Kümeleme yöntemi ele alınmıştır.
Bu yöntemlerle Türkiye’deki üç ayrı yıla ait trafik kaza verileri kullanılarak
oluşturulan sınıflar ve üretilen çok değişkenli haritalar kullanılarak bu
yöntemlerin karşılaştırılması yapılmış, bu yöntemlerle üretilen haritaların
risk yönetimi ve planlamada kullanılabilirliği üzerinde durulmuştur.

Keywords

Çok değişkenli haritalama, veri madenciliği, kümeleme analizi

USING CLUSTER ANALYSIS METHODS FOR MULTIVARIATE MAPPING

Abstract

   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.

Keywords

Multivariate mapping, data mining, cluster analysis

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