Parametric optimisation in a 2-D cellular automata model of fundamental seismic attributes with the use of genetic algorithms

A two-dimensional (2-D) cellular automata (CA) dynamic system constituted of cells-charges has been proposed for the simulation of the earthquake process. In this paper, the study is focused on the optimal parameterisation of the model introducing the use of genetic algorithm (GA). The optimisation of the CA model parameterisation, by applying a standard GA, extends its ability to study various hypotheses concerning the seismicity of the region under consideration. The GA evolves an initially random population of candidate solutions of model parameters, such that in time appropriate solutions to emerge. The quality criterion is realised by taking into account the extent that the simulation results match the Gutenberg–Richter (GR) law derived from recorded data of the area under test. The simulation results presented here regard regions of Greece with different seismic and geophysical characteristics. The results found are in good quantitative and qualitative agreement with the GR scaling relations.