CTBT: Science and Technology Conference 2025 - SnT2025

Machine-Learning Event Classification in North-East China Using Augmented Data

P2.1-836

Not scheduled

20m

Zeremoniensaal

E-poster T2.1 Characterization of Treaty-Relevant Events P2.1 Characterization of Treaty-Relevant Events

Speaker

Mr Alemayehu Jemberie (Air Force Technical Applications Center (AFTAC))

Description

A transfer learning approach was adopted, using a VGG16 neural network model to classify earthquakes from non-earthquake events in North-East China, close to the North Korean test site. Magnitudes below 4 are considered for classification of tectonic events (earthquakes) from explosions. Because of the scarcity of observed explosion data, synthetic seismograms were generated using SW4 to augment the observed data so that overfitting doesn’t happen during validation. Our preliminary experiment shows promising results which may help us identify any potential future small event.