Deep Learning Approach in Seismology: Enhancing Earthquake Forecasting using K-Means Clustering and LSTM Networks

Located in the subduction zone of four tectonic plates, the high occurrence of seismic events is a severe threat in Indonesia. Mitigating the adverse effects of such disasters is essential to forecast the likelihood of future earthquakes. Consequently, developing a robust method of forecasting futu...

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Bibliographic Details
Main Authors:	Tyanita Puti Marindah Wardhani, Zulkifli Tahir, Elly Warni, Anugrayani Bustamin, Muhammad Alief Fahdal Imran Oemar, Muhammad Alwi Kayyum
Format:	Article
Language:	English
Published:	UUM Press 2025-01-01
Series:	Journal of ICT
Subjects:	Deep learning earthquake forecasting LSTM spatial distribution seismology
Online Access:	https://e-journal.uum.edu.my/index.php/jict/article/view/24382
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Deep Learning Approach in Seismology: Enhancing Earthquake Forecasting using K-Means Clustering and LSTM Networks

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