April 16, 2025

Reza Mansoori

Academic Rank: Assistant professor
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Faculty: Faculty of Nano and Biotechnology

Research

Title
Enhanced Earthquake Location using Deep Learning
Type Presentation
Keywords
Earthquake, Waveform, Localization, Data generation, Deep learning.
Researchers parviz khorsand (First researcher) , Reza Mansoori (Second researcher) , Mohammad Shokri-Kaveh (Third researcher) , Saeed Soltani-moghadam (Fourth researcher)

Abstract

Due to the complexity of the earthquake occurrence process and the lack of specific patterns, accurate prediction earquake location presents several challenges. However, recent studies have shown that neural networks can play a key role in earthquake data analysis, particularly in determining the exact locations of earthquakes. In this research, aimed at improving earthquake localization, earthquake data were collected from the Iranian Seismological Center, and the waveform of each earthquake was converted into images. Subsequently, these images were labeled with spatial information (latitude, longitude, and depth), and the location of each earthquake was modeled in three dimensions using a Gaussian function. Finally, a labeled earthquake dataset was created that will be used to train neural networks.