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Representing Earthquake Accelerogram Records for Cnn Utilization

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Date

2020

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Ieee

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Green Open Access

No

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No
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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.

Description

Keywords

Earthquake Accelograms, Epicenter Clustering, Convolutinal Neural Networks, Signal processing, Silver, Clustering algorithms, Convolutinal Neural Networks, Earthquake records, Spectrograms, False color, Convolution, Graphic methods, ITS applications, Earthquakes, Earthquake Accelograms, Convolutional neural networks, Epicenter Clustering, Accelerograms, Convolutional networks

Fields of Science

0211 other engineering and technologies, 02 engineering and technology, 0201 civil engineering

Citation

Çıkış, Melis; Tileyoglu, Salih; Akagunduz, Erdem (2020). "Representing Earthquake Accelerogram Records for CNN Utilization", 28th Signal Processing and Communications Applications Conference, SIU 2020Gaziantep5 October 2020through 7 October 2020.

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Source

28th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORK

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1

End Page

4
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Scopus : 0

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4

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