Prediction of Aftershocks Distribution Using Self-Organizing Feature Maps (SOFM) and Its Application on the Birjand-Ghaen and Izmit Earthquakes

Self-Organizing Feature Maps (SOFM) have become powerful intelligent tools in recent years, used widely in pattern recognition and data clustering [۵]. This paper has shown that SOFM can be used to predict the concentration and the trend of aftershocks of ۱۹۹۷ Birjand-Ghaen, Iran and ۱۹۹۹ Izmit, Turkey earthquakes. The present experiments using SOFM confirmed the algorithm could be applied for the prediction of local distribution of aftershock region.

Keywords:

Self-Organizing Feature Maps , Aftershocks , prediction , Clustering , Concentration