A Decision Support System for Classification and Recognition of Earthquakes and Explosions

摘要：

This paper introduces current advances and some rudimental results of our ongoing research project. To discriminate between earthquakes and explosions, temporal and spectral features extracted from seismic waves～ plus some seismological parameters (such as epicenter depth, location,magnitude) are crux for rapid and correct recognmng event sources (earthquakes or explosions). Seismological parameters are used as the first step to screen out obvious earthquake events.Fourier transforms (FFD, 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 (>95％). If more temporal and spectral features are utilized properly, more robust recognition result is surely possibility.

关键词： explosion eurtiIWmke tenrpo-specOvzt feutureS clussifi-cotiorr SVC

作者: HUANG Hanming BI Ming Xia SHI Xinhua ZHOU Haijun Zhao Jing CHEN Yinyan BIAN Yin Ju

作者单位: College of Computer Science & Information Engineering Guangxi Normal University Guilin. China. 54100 Institute of Geophysics China Seismological Burea Beijing, China. 100081

会议类型: 国际会议

会议名称: The 2nd International Conference on Software Engineering and Data Mining(IEEE 第二届国际软件工程和数据挖掘学术大会 SEDM 2010)

会议地点: 成都

会议语种:英文

页码: 247-250

在线出版日期: 2010-06-23（万方平台首次上网日期，不代表论文的发表时间）