earthquake prediction based on spatio-temporal datamining an lstm network approach
Diwakar.M.G,Ram Kumar.V,Parthasarathy.P
Published in International Journal of Advanced Research in Computer Networking,Wireless and Mobile Communications
ISSN: 2320-7248 Impact Factor:1.8 Volume:5 Issue:3 Year: 21 April,2025 Pages:250-255
Abstract
The importance of seismological research around the globe is very clear. Therefore, new tools and algorithms are needed in order to predict magnitude, time, and geographic location, as well as to discover relationships that allow us to better understand this phenomenon and thus be able to save countless human lives. However, given the highly random nature of earthquakes and the complexity in obtaining an efficient mathematical model, efforts until now have been insufficient and new methods that can contribute to solving this challenge are needed. In this work, a novel earthquake magnitude prediction method is proposed, which is based on the composition of a known system whose behavior is governed according to the measurements of more than two decades of seismic events and is modeled as a time series using machine learning, specifically a network architecture based on LSTM (long short term memory) cells.
Kewords
EARTHQUAKE PREDICTION, BASED ON SPATIO-TEMPORAL and NETWORK APPROACH.
Reference
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