investigating the precision of seismic data in iran kope-dagh seismic province using artificial statistical method

Past earthquakes data are crucial for conducting earthquake hazard analyses, primarily integrated into probabilistic seismic hazard analysis (psha) through the gutenberg-richter (g-r) relationship. seismicity data is typically represented in regional seismic catalogs; however, these catalogs often contain gaps, leading to uncertainties in the data. the parameters derived from the g-r relationship are significantly influenced by these incomplete datasets, which in turn affect subsequent psha calculations. in this study, we apply an artificial statistical method (asm) to estimate the missing values in the kope-dagh seismic catalog of iran. this method leverages total probability theory and bayes' theorem to create a more comprehensive dataset, referred to as the stochastic synthetic seismic catalog (sssc). by comparing the completed catalog with the original datasets, we will present the ratio of data availability across different time intervals. this analysis will provide insights into the reliability of seismicity data for the kope-dagh seismic province over various periods.