Konferans bildirisi Erişime Kapalı

Characterization of the Earthquakes in the Aegean Region of Turkey via Shannon Entropy

2022    Özel, Gamze; Karakavak, Hatice Nur; Tekin, Senem

Shannon entropy, also known as information entropy or the Shannon entropy index, is a measure of the degree of randomness in a set of data. It is used to calculate the uncertainty that comes with a certain character appearing next in a string of text. The more characters there are, or the more proportional are the frequencies of occurrence, the harder it will be to predict what will come next resulting in an increased entropy. When the outcome is certain, the entropy is zero.Apart from information theory, Shannon entropy is used in many fields. Ecology, genetics, seismology and computer sciences are just some of them. The occurrence of earthquakes can be classified as a random event and can be described using entropy since earthquakes are random events characterized by a large degree of uncertainty. Hence, entropy can play an important role in seismic description. In recent years, seismicity has increased considerably in the Aegean Region of Turkey and there have been earthquakes in which people lost their lives. For this reason, analysis of this region is essential since West Turkey is one of the most seismically active regions of Turkey. In this study, Shannon entropy has been used to analyze magnitude and depth of the earthquakes occurred in the Aegean Region of Turkey. Marginal and conditional entropy values are calcuted for both of the parameters. Approximate and sample entropies are also obtained for the Aegean Region of Turkey.