The results of the application of an unsupervised learning (neural network) approach comprising a Self Organizing Map (SOM), to distinguish micro-earthquakes from quarry blasts in the vicinity of Istanbul, Turkey, are ...

Two unsupervised pattern recognition algorithms, k-means, and Gaussian mixture model (GMM) analyses have been applied to classify seismic events in the vicinity of Istanbul. Earthquakes, which are occurring at different ...

Identification and classification of different seismo-tectonic events with similar characteristics in a region of interest is one of the most important subjects in seismic hazard studies. In this study, linear and nonlinear ...

In this study, we investigated waveforms of 179 seismic events (1.8 < Md < 3.0) from the KOERI, NEMC digital database. We determined differences between earthquakes and quarry blasts based on time- and frequency-domain ...

The purpose of this article is to demonstrate the use of feedforward neural networks (FFNNs), adaptive neural fuzzy inference systems (ANFIS), and probabilistic neural networks (PNNs) to discriminate between earthquakes ...

[1] Aftershocks of the 17 August 1999, Mw = 7.4, Kocaeli earthquake were used to investigate the large-amplitude SmS arrivals in the Sea of Marmara. We produced the event record sections from the transverse components of ...