FastGTWR: Hızlı coğrafi ve zamansal ağırlıklı regresyon yaklaşımı

Yıl 2021, Cilt: 36 Sayı: 2, 715 - 726, 05.03.2021

Murat Taşyürek Mete Çelik

https://doi.org/10.17341/gazimmfd.757131

Cited By: 4

Öz

Mekânsal analizler günümüzde önemli hale gelmiştir ve çok farklı uygulama alanlarında kullanılmaktadır. Yaygın olarak kullanılan konum temelli analiz yöntemlerinden biri olan Coğrafi Ağırlıklı Regresyon (Geographically Weighted Regression-GWR) coğrafya üzerindeki değişen ilişkileri modellemek için kullanılan bir yerel mekânsal regresyon tekniğidir. Coğrafi ve Zamansal Ağırlıklı Regresyon (Geographically and Temporal Weighted Regression-GTWR) ise GWR yaklaşımının verideki zamansal ilişkileri gözönüne almasıyla geliştirilen bir yaklaşımdır.Veri kümesinde mekân-zamansal heterojenliğin olduğu durumlarda GTWR yaklaşımı GWR yaklaşımına göre daha iyi modeller üretmesine rağmen mekân-zamansal modellerin karmaşıklığı göz önüne alındığında algoritma zaman karmaşıklığı artmaktadır. Bu nedenle, literatürde koşturulan GTWR modelleri sınırlı sayıdaki veri üzerinde çalışabilmiştir. Bu çalışmada GTWR’nin algoritmasının hızını arttırmak ve dolayısı ile veri boyutu kısıtlamasının üstesinden gelmek için hızlı bir GTWR yaklaşımı olan FastGTWR modeli önerilmiştir. Önerilen FastGTWR yaklaşımının performansı gerçek veriler kullanılarak klasik GWR ve GTWR yaklaşımlarının performanslarıyla karşılaştırılmıştır. Deneysel sonuçlar önerilen FastGTWR yaklaşımının GWR ve GTWR yaklaşımlarına göre daha hızlı çalıştığını ortaya koymuştur.

Anahtar Kelimeler

Coğrafi ağırlıklı regresyon, Mekansal veri madenciliği, zamansal veri madenciliği, FastGTWR

Teşekkür

Meteoroloji Genel Müdürlüğü'ne verileri bizimle paylaştığı için teşekkür ederiz.

Kaynakça

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