Discrimination of earthquakes and quarries in the Edirne district (Turkey) and its vicinity by using a linear discriminate function method and artificial neural networks

Abstract

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 Bogazici 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.