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 ...

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 ...

The aims of this study are to estimate soil attenuation using alternatives to traditional methods, to compare results of using these methods, and to examine soil properties using the estimated results. The performances of ...

In this paper, two different Artificial Neural Network (ANN) techniques, namely the Feed-Forward Neural Networks (FFNNs) and the Radial Basis Function Neural Networks (RBFNNs), are used for the prediction of the daily water ...