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Open Geosciences

formerly Central European Journal of Geosciences

Editor-in-Chief: Jankowski, Piotr

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Prediction of earthquake hazard by hidden Markov model (around Bilecik, NW Turkey)

Ceren Can / Gul Ergun / Candan Gokceoglu
Published Online: 2014-08-06 | DOI: https://doi.org/10.2478/s13533-012-0180-1


Earthquakes are one of the most important natural hazards to be evaluated carefully in engineering projects, due to the severely damaging effects on human-life and human-made structures. The hazard of an earthquake is defined by several approaches and consequently earthquake parameters such as peak ground acceleration occurring on the focused area can be determined. In an earthquake prone area, the identification of the seismicity patterns is an important task to assess the seismic activities and evaluate the risk of damage and loss along with an earthquake occurrence. As a powerful and flexible framework to characterize the temporal seismicity changes and reveal unexpected patterns, Poisson hidden Markov model provides a better understanding of the nature of earthquakes. In this paper, Poisson hidden Markov model is used to predict the earthquake hazard in Bilecik (NW Turkey) as a result of its important geographic location. Bilecik is in close proximity to the North Anatolian Fault Zone and situated between Ankara and Istanbul, the two biggest cites of Turkey. Consequently, there are major highways, railroads and many engineering structures are being constructed in this area. The annual frequencies of earthquakes occurred within a radius of 100 km area centered on Bilecik, from January 1900 to December 2012, with magnitudes (M) at least 4.0 are modeled by using Poisson-HMM. The hazards for the next 35 years from 2013 to 2047 around the area are obtained from the model by forecasting the annual frequencies of M ≥ 4 earthquakes.

Keywords: Hidden Markov Model; Poisson Process; EM Algorithm; Bilecik

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About the article

Published Online: 2014-08-06

Published in Print: 2014-09-01

Citation Information: Open Geosciences, Volume 6, Issue 3, Pages 403–414, ISSN (Online) 2391-5447, DOI: https://doi.org/10.2478/s13533-012-0180-1.

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