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Application of artificial neural network and logistic regression methods to landslide susceptibility mapping and comparison of the results for the ulus district, Bartin Bartin, ulus ilçesi için yapay sinir aǧi ve lojistik regresyon yöntemlerinin heyelan duyarlilik çalişmasina uygulanmasi ve karşilaştirilmasi
Date
2012-03-01
Author
Eker, Arif Mert
Dikmen, Mehmet
Cambazoǧlu, Selim
Düzgün, Şebnem H.s.b.
Akgün, Haluk
Metadata
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Bu çalışma, Coğrafi Bilgi Sistemlerine (CBS) dayalı lojistik regresyon (LR) ve yapay sinir ağı (YSA) analizlerini kullanarak, Karadeniz bölgesindeki Bartın ilinin Ulus ilçesi için bir heyelan duyarlılık haritası hazırlamayı amaçlamaktadır. Bu araştırma kapsamında, Maden Tetkik ve Araştırma Genel Müdürlüğü tarafından hazırlanan heyelan envanter haritası, heyelan sınıflandırma haritasına temel olarak alınmıştır. Çalışma alanındaki analizlerin tamamı aktif heyelanlara istinaden gerçekleştirilmiştir. Bununla birlikte, on dört açıklayıcı değişken CBS’de sayısallaştırılmış, birleştirilmiş ve düzenlenmiştir. Çalışma alanı 250 m x 250 m’lik hücrelere bölünmüş ve heyelan envanter bilgisinin, alan üzerindeki yayılımının daha anlamlı bir popülasyon dağılımı göstermesini sağlamak için çekirdek (Kernel) yoğunluğu yöntemi uygulanmış, tüm değişkenler, oluşturulmuş olan bu envanter verisine dahil edilmiştir. Bağımlı değişken, kalibrasyon ve doğrulama olarak iki veri setine ayrılmıştır. Bağımlı ve bağımsız değişkenler arasındaki ilişkiyi bulmak ve farklı tekniklerin oluşturduğu heyelan duyarlılık bölgelemesi sonuçlarını karşılaştırıp en uygun duyarlılık yöntemini değerlendirmek için LR ve YSA olmak üzere iki farklı yöntem kullanılmıştır.
Subject Keywords
Heyelan duyarlılığı,
,
Lojistik regresyon
,
Yapay sinir ağı
,
Ulus
,
Bartın
,
Landslide susceptibility
,
Logistic regression
,
Artificial neural network
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84859360838&origin=inward
https://hdl.handle.net/11511/82691
Journal
Journal of the Faculty of Engineering and Architecture of Gazi University
Collections
Department of Geological Engineering, Article
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The purpose of this study was to investigate the capabilities of different landslide susceptibility methods by comparing their results statistically and spatially to select the best method that portrays the susceptibility zones for the Ulus district of the Bartin province (northern Turkey). Susceptibility maps based on spatial regression (SR), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression (LR) method, and artificial neural network method (ANN) were generated,...
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BibTeX
A. M. Eker, M. Dikmen, S. Cambazoǧlu, Ş. H. s. b. Düzgün, and H. Akgün, “Application of artificial neural network and logistic regression methods to landslide susceptibility mapping and comparison of the results for the ulus district, Bartin Bartin, ulus ilçesi için yapay sinir aǧi ve lojistik regresyon yöntemlerinin heyelan duyarlilik çalişmasina uygulanmasi ve karşilaştirilmasi,”
Journal of the Faculty of Engineering and Architecture of Gazi University
, pp. 163–173, 2012, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84859360838&origin=inward.
