Magnitude Type Conversion Models for Earthquakes in Turkey and Its Vicinity with Machine Learning Algorithms

In this study, three new regression models are created for magnitude-type conversion with different machine learning algorithms (linear regression, regression trees, support vector machines, Gaussian process regression models, ensembles of trees) by using the earthquakes (M >= 4.0) that occurred in Turkey (1900-2020). Additionally, eight new equations are formed with linear and orthogonal regression methods. Developed equations and models are compared to equations selected from the literature by test data. As a result of the study, it is observed that machine learning algorithms create better models and provide results closer to the real values than created and selected equations.