When the Earth Speaks: MACREE's Intelligent Separation of Quakes and Blasts

Authors

  • Hadia Azmat

Keywords:

Seismic event classification, MACREE, earthquake detection, explosion detection, machine learning, signal processing, feature extraction, time-frequency analysis, seismic monitoring, hybrid classification model

Abstract

Seismic event classification plays a pivotal role in understanding Earth’s movements, from earthquakes to human-made explosions. Distinguishing between these events is critical for both natural disaster management and international security, particularly in the context of nuclear test monitoring. However, traditional seismic detection methods often struggle to accurately differentiate between the seismic waves generated by earthquakes and explosions. This paper introduces MACREE (Modular Analysis for Classification and Refined Event Evaluation), a novel system designed to intelligently separate earthquakes from explosions. By combining advanced signal processing techniques with machine learning algorithms, MACREE enhances the accuracy of seismic event classification. It employs time-frequency analysis, feature extraction, and an adaptive classification model to analyze seismic signals and distinguish between different types of events. The paper discusses MACREE's architecture, methodologies, and its potential applications in disaster response, nuclear test ban verification, and environmental monitoring.

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Published

2020-06-30

How to Cite

Hadia Azmat. (2020). When the Earth Speaks: MACREE’s Intelligent Separation of Quakes and Blasts. MZ Computing Journal, 1(1), 17–24. Retrieved from http://mzresearch.com/index.php/MZCJ/article/view/477

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