MACREE – A Modern Approach for Classification and Recognition of Earthquakes and Explosions
Though many systems are available for discrimination between earthquakes and explosions, our introduces new advances and some rudimental results of our ongoing research project. To discriminate between earthquakes and explosions, temporal and spectral features extracted from seismic waves, additional some seismological parameters (such as epicenter depth, location, magnitude) are crux for rapid and correct recognizing event sources (earthquakes or explosions). Seismological parameters are used as the first step to screen out obvious earthquake events. Fourier transforms (FFT), chirp-Z transforms, wavelet transforms have been conducted and some prominent features are acquired by present experimental dataset. In some experiments, wavelet features plus support vector classification (SVC) have reached very high correct recognition rate (>90%). This proposed paper can be used in evolving scenarios.
KeywordsClassification Recognition Earthquake Explosion Tempo-Spectral features Support Vector Machines (SVC)
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