Chaotic Dynamics and Analysis with Artificial Neural Networks of Aftershocks of 2019 Silivri Earthquake

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dc.contributor.authorAydogmus, Fatma
dc.contributor.authorOniz, Yesim
dc.contributor.authorSimuratli, Eljan
dc.contributor.authorTosyalı, Eren
dc.contributor.authorKaplanvural, Ismaıl
dc.contributor.authorMutlu, Ahu Kömeç
dc.contributor.authorÖnem, Zeynep Çiçek
dc.date.accessioned2026-04-04T18:44:24Z
dc.date.available2026-04-04T18:44:24Z
dc.date.issued2024
dc.departmentİstanbul Bilgi Üniversitesi
dc.description.abstractEarthquakes, whose physical, economic, psychological, and social damages can last for many years, are of vital importance for Türkiye, which is located in the most active earthquake zone that causes many earthquakes in the world. The North Anatolian Fault (NAF) is one of Türkiye's most important tectonic elements as it is the world’s fastest-moving right-lateral and strike-slip active fault zone consisting of many segments. The recent 5.8 magnitude 2019 Silivri earthquake, which occurred in the part of the NAF zone crossing the Marmara Sea, is an indicator that earthquake activity continues in the region. Aftershocks play a crucial role in seismicity research and seismic hazard assessments in terms of providing data and usable information in the examination of seismic dynamics with the changes observed in their time-dependent behavior and regional distribution. In this study, the aftershocks of the Silivri earthquake were examined as a natural laboratory using nonlinear analysis methods. Within the scope of the study, aftershocks of the Silivri earthquake were analyzed with a hybrid artificial neural network as well as different neural network structures, and for this purpose, data from 361 aftershocks with a magnitude greater than 1.5 in the year following the earthquake were used.
dc.identifier.doi10.54287/gujsa.1569701
dc.identifier.endpage741
dc.identifier.issn2147-9542
dc.identifier.issue4
dc.identifier.startpage732
dc.identifier.trdizinid1290149
dc.identifier.urihttps://doi.org/10.54287/gujsa.1569701
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1290149
dc.identifier.urihttps://hdl.handle.net/11411/10133
dc.identifier.volume11
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofGazi University Journal of Science Part A: Engineering and Innovation
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_TR-Dizin_20260402
dc.subjectChaos Theory, Artificial Neural Network, Time Series, Aftershock
dc.titleChaotic Dynamics and Analysis with Artificial Neural Networks of Aftershocks of 2019 Silivri Earthquake
dc.typeArticle

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