In this paper, the Markov chain approach is applied to 108 years of earthquake data recorded at Kandilli Observatory since a signicant portion of Turkey is subject to frequent earthquakes.
📌 3 Key Takeaways
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Objective & Hypothesis:The Markov chain is a probabilistic model used with stochastic processes in many branches of science such as seismology, biology, meteorology and hydrology.
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Key Findings & Data:This model is utilized to evaluate modeling of an event and allows the use of combinatorial probability estimates including initial and transitional probabilities.
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Conclusion & Impact:In this paper, the Markov chain approach is applied to 108 years of earthquake data recorded at Kandilli Observatory since a signicant portion of Turkey is subject to frequent earthquakes.
The Markov chain is a probabilistic model used with stochastic processes in many branches of science such as seismology, biology, meteorology and hydrology. This model is utilized to evaluate modeling of an event and allows the use of combinatorial probability estimates including initial and transitional probabilities. These probabilities contain useful information that can be used in earthquake modelling. In this paper, the Markov chain approach is applied to 108 years of earthquake data recorded at Kandilli Observatory since a signicant portion of Turkey is subject to frequent earthquakes.
OZEL, G., SOLMAZ, A. (2012). Türkiye'de Deprem Tekrarlanma Zamanının Tahmini ve Neotektonik Bölgelere Göre Depremselliğin Markov Zinciri ile İncelenmesi. Cankaya University Journal of Science and Engineering, Cilt: 9 - Sayı: 2, 1–1. https://ajindex.com/articles/746073
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