  A method that exactly knows the earthquakes beforehand and can generalize
them cannot still been developed. However, earthquakes are tried to be
predicted through numerous methods. One of these methods, artificial neural
networks give appropriate outputs to different patterns by learning the
relationship between the determined inputs and outputs. In this study, a
feedforward back propagation artificial neural network that is connected to
Gutenberg-Richter relationship and that bases on b value used in earthquake
predictions was developed. The artificial neural network was trained employing
earthquake data belonging to four different regions which have intensive
seismic activity in the west of Turkey. After the training process, the
earthquake data belonging to later dates of the same regions were used for
testing and the performance of the network was put forward. When the prediction
results of the developed network are examined, the prediction results that the
network predicts that an earthquake is not going to occur are quite high in all
regions. Furthermore, the earthquake prediction results that the network
predicts that an earthquake is going to occur are different to some extent for
the studied regions.
