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Identification of pre-seismic radon anomaly using artificial neural network near Indo-Burman subduction line.

Authors :
Thuamthansanga, T.
Tiwari, Ramesh Chandra
Source :
Journal of Radioanalytical & Nuclear Chemistry. Nov2024, Vol. 333 Issue 11, p5519-5529. 11p.
Publication Year :
2024

Abstract

The study presents analysis of 1 year 15 min cycle radon data using artificial neural network (ANN) in an attempt to estimate earthquake prediction time near Indo-Burman subduction line. The region was found to be seismically active and radon anomalies respond well to it, when majority of the radon anomalies peaks and selected earthquakes correlated. The observation also shows that application of non-linear technique ANN to a non-linear data like radon seems a promising approach in predicting geophysical phenomena at one of the most seismically active region of the world. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02365731
Volume :
333
Issue :
11
Database :
Academic Search Index
Journal :
Journal of Radioanalytical & Nuclear Chemistry
Publication Type :
Academic Journal
Accession number :
180518614
Full Text :
https://doi.org/10.1007/s10967-024-09487-6