Determination of Earthquake Focal Mechanism Using Artificial Intelligence

Focal mechanism solution is important to analyze faulting type, fault geometry, and to evaluate aftershock patterns after a devastating earthquake occurs. Focal mechanisms were obtained by S/P amplitude ratios and P wave polarities, are fundamental data to investigate the geometry of fault zone, slip size, and the crustal stress field. Methods for solving the focal mechanism, have categories such as full waveforms, first motions of P waves, amplitudes of P or S waves, based on the waveform information used. In this study, we applied artificial intelligence to solve the focal mechanisms of small earthquakes in Izmir and its surroundings, where there is high microearthquake activity. The data set required for artificial intelligence applications was generated by using the records of earthquake stations located in western Turkey, especially in Izmir and its surroundings. Focal mechanism solution for Buca earthquake was determined by using Artificial neural networks are a branch of artificial intelligence. We compare the results obtained with artificial intelligence and traditional methods, and it is seen that artificial intelligence can be applicable for the focal mechanism solutions.