| Abstract: | Hazard assessment of dangerous natural phenomena is critical because of their evident results concerning loss of human life and property, especially in dense populated areas. Earthquakes are probably the most devastating phenomenon since their immediate and long-term consequences are severe. This study is focused on the earthquake data analysis in different regions of Greece, characterised by different seismicity levels. In specific, a novel model is proposed based on evolutionary computation methods, such as symbolic regression by genetic programming and genetic algorithms in order to elucidate preliminary hidden mathematical relations and patterns found in the seismological signals under study. Furthermore, the model is calibrated using reverse engineering and closes the loop from the data collection to initial hypothesis. In this way, the model formation is achieved. The presented simulation results qualitatively and quantitatively reveal some of the fundamental characteristics of each studied geographical region located in Greece that stem from its geodynamic properties. |
