| Autor: |
Chandrakumar, Chanthujan, Tan, Marion Lara, Holden, Caroline, Stephens, Max T., Prasanna, Raj |
| Zdroj: |
Earth Science Informatics; Jan2025, Vol. 18 Issue 1, p1-11, 11p |
| Abstrakt: |
What is the most effective P-wave detection algorithm for an Earthquake Early Warning (EEW) system that minimises false, late and missed detections? This study evaluates the performance of four distinct P-wave detection algorithms in terms of their detection accuracy. Utilising a comprehensive MEMS-based ground motion dataset from the GeoNet network, this study analyses the algorithms’ performances by introducing four distinct pick deviation categories. Among the evaluated algorithms, the wavelet-based P-wave picker is identified as the most suitable and accurate for EEW systems, achieving a 98.3% success rate with a mean deviation of 0.12 s and a standard deviation of 0.63 s compared to the manual pick. This algorithm proves effective for both community-engaged and traditional EEW systems. The methodology used for performance comparison in this research is applicable to other regions and datasets, aiding in selecting more accurate and reliable P-wave detection algorithms. The study suggests extending this performance analysis to encompass a broader spectrum of traditional and modern algorithms in future research. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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