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MACREE - A Modern Approach for Classification and Recognition of Earthquakes and Explosions

机译:宏观 - 一种分类和识别地震和爆炸的现代方法

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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.
机译:虽然许多系统可用于地震和爆炸之间的歧视,但我们介绍了我们正在进行的研究项目的新进展和一些无论如例。为了区分地震和爆炸之间,从地震波提取的时间和光谱特征,额外的一些地震参数(如震中深度,位置,幅度)是用于快速和正确识别事件来源的症状(地震或爆炸)。地震参数用作筛选明显地震事件的第一步。已经进行了傅里叶变换(FFT),Chirp-Z变换,已经进行了小波变换,并且通过现有的实验数据集获取了一些突出的特征。在一些实验中,小波特征加支持载体分类(SVC)达到了非常高的正确识别率(> 90%)。该提出的纸张可用于不断发展的情况。

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