Seismic hazard model of the region of Iraq and its around using machine learning techniques by python language

This study for the first time developed a Robust Multi-Output machine learning regression model for seismic hazard zone of Iraq and around regions using constructed 3-D shear-wave velocity (Vs), seismic tomography dataset model for the crust and uppermost mantle beneath the study area. This work for the first time Calculated Peak Crust Acceleration (PCA) for seismic hazard analysis by Considering the transmitted initial seismic energy through the Earth's crust layers from hypocenter. discovered the inverse relation between calculated PCA and the density of crust and related this relation to seismic activity of study area. We have derived some physical equations for extraction of many variables as inputs for our final machine learning model based on reliable understanding of the tomography data to physical variables by preparing hug dataset from different physical conditions of crust. All machine learning and deep learning algorithms in this study wrote by python language using anaconda platform the open-source Individual Edition (Distribution).