Representing Earthquake Accelerogram Records for Cnn Utilization

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2020

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Cikis, Melis
Tileyoğlu, Salih
Akagündüz, Erdem

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IEEE

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Abstract

In this study, a spectrogram based false color representation of earthquake accelergrams is proposed and its usability for both human investigation and its application in convolutional networks are discussed. By using more than forty two thousand earthquake records open to the public, an epicenter clustering algorithm was employed, and it was observed that earthquakes in similar clusters produce similar representations. The prospective purpose of the proposed representation is to estimate the epicenter of an earthquake by processing the accelerograms recorded in a single station using convolutional networks.

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Convolutinal Neural Networks, Epicenter Clustering, Earthquake Accelograms

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