ARTIFICIAL NEURAL NETWORK MODELLING OF EARTHQUAKES AROUND USAK CITY

Yıl 2017, Cilt: 19 Sayı: 56, 378 - 388, 01.05.2017

Elif Çağda Kandemir Mazanoğlu

Öz

In Turkish Earthquake Code 2007 (TEC, 2007), Usak city is located in the second-degree seismic zone while Esme, a town and district of Usak Province, is in the first-degree seismic zone. However cities in neighbourhood of Usak, such as Gediz, Simav towns of Kütahya city and Dinar district of Afyon city have many active faults which led to severe seismic damages in and around Usak. Despite this, Usak has only 2 active seismic stations which are in Usak city centre and Esme town. This paper aims to constitute artificial neural network (ANN) models by using seismic data of neighbour stations and to estimate peak ground acceleration (PGA) in the districts without stations. The results of models are validated by comparing the predicted and measured seismic data of the Usak central station. In addition, PGAs obtained by models are compared with design values in TEC 2007

Anahtar Kelimeler

Artificial Neural Network, Peak Ground Acceleration, Feed Forward Back-Propagation Algorithm

UŞAK İLİ ÇEVRESİNDEKİ DEPREMLERİN YAPAY SİNİR AĞLARI İLE MODELLENMESİ

Öz

Deprem Bölgelerinde Yapılacak Binalar Hakkında Yönetmelik 2007 (DBYBHY, 2007)’de, Uşak ilinin büyük bir kısmı 2. derece deprem bölgesinde olup, Eşme ilçesi 1. derece deprem bölgesinde bulunmaktadır. Ancak il sınırlarına yakın çevrede bulunan Kütahya’ya bağlı Gediz, Simav ve Afyon’a bağlı Dinar ilçelerindeki uzun ve aktif faylarda meydana gelen depremler, Uşak il ve ilçelerinde önemli ölçüde hissedilmekte ve etkileri gözlenmektedir. Buna karşın il sınırları içerisinde, biri merkezde diğeri Eşme’de olmak üzere yalnızca 2 adet deprem kayıt istasyonu bulunmaktadır. Çalışmada hedeflenen, çevredeki deprem kayıt istasyonlarında ölçülmüş kayıtlar kullanılarak, yapay sinir ağları (YSA) modelleri oluşturmak ve il sınırları içinde istasyon olmayan bölgelerdeki en büyük yer ivmesi tahmini yapabilmektir. Oluşturulan modeller kullanılarak istasyon olan merkez ilçede meydana gelmiş en yüksek ivme değerleri tahmin edilmiş ve ölçülmüş veriler ile karşılaştırılmış, böylece modellerin doğruluğu irdelenmiştir. Buna ek olarak, tüm ilçeler için elde edilen en büyük yer ivmesi değerleri DBYBHY 2007’de öngörülen değerler ile kıyaslanmıştır

Anahtar Kelimeler

Yapay Sinir Ağları, Maksimum Yer İvmesi, İleri Beslemeli Geri-Yayılım Algoritması

Kaynakça

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