首页> 外文期刊>Acta Geophysica >Discrimination of earthquakes and quarries in the Edirne district (Turkey) and its vicinity by using a linear discriminate function method and artificial neural networks
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Discrimination of earthquakes and quarries in the Edirne district (Turkey) and its vicinity by using a linear discriminate function method and artificial neural networks

机译:利用线性区分函数方法和人工神经网络歧视Edirne区(土耳其)及其附近的地震和争吵

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In this study, seismic events in the Edirne district (Turkey) and its vicinity have been investigated in order to discriminate earthquakes from quarry blasts. A total of 150 seismic events with Md?≤?3.5 duration magnitude from a seismic activity catalog between 2009 and 2014 recorded by the Enez (ENEZ), Erikli (ERIK) and Gelibolu (GELI) broadband stations operated by Bo?azi?i University, Kandilli Observatory and Earthquake Research Institute Regional Earthquake-Tsunami Monitoring Center were used in this study. The maximum S-wave and maximum P-wave amplitude ratio of vertical component velocity seismograms, power ratio (Complexity) and total signal duration of the waveform were calculated. Earthquakes and quarry blasts were discriminated using the linear discriminate function (LDF) and back propagation feed forward neural networks, an artificial neural network (ANN) learning algorithm, taking the determination coefficient and variance account values between these parameters into consideration. Eighty-one (54%) of the total 150 seismic events studied were determined to be earthquakes, and sixty-nine (46%) of them were determined to be quarry blasts. The LDF and ANNs methods were applied to the data in Edirne and its vicinity using a pair of parameters and were compared to each other for the first time. The accuracy of the methods are 95% and 99% for LDF and ANNs, respectively.
机译:在这项研究中,已经调查了Edirne区(土耳其)的地震事件及其附近,以区分Quarry Blasts的地震。总共150例与MD?≤3.5持续时间来自2009年至2014年的地震活动目录,由Enez(ENEZ),Erikli(Erik)和Gelibolu(Geli)宽带站由Bo?Azi(Erik)和Gelibolu(Geli)宽带站? ,本研究中使用了Kandilli天文台和地震研究院区域地震 - 海啸监测中心。计算垂直分量速度地震图,功率比(复杂性)和波形的总信号持续时间的最大S波和最大P波振幅比。使用线性区分功能(LDF)和后传播馈送前神经网络,一个人工神经网络(ANN)学习算法,参考这些参数之间的确定系数和方差账户值考虑,参考地震和采石场爆炸。研究的八十一(54%)学习的150例(54%)被确定为地震,60九(46%)被确定为采石场。使用一对参数对LDF和ANNS方法应用于Edirne及其附近的数据,并首次相互比较。 LDF和ANN的方法的准确性分别为95%和99%。

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