TY - JOUR AU - DENİZ BAŞAR, Ozlem AU - GÜNEREN GENÇ, Elif PY - 2020/08/05 Y2 - 2024/03/29 TI - A COMPARISON OF LOGISTIC REGRESSION, ARTIFICIAL NEURAL NETWORKS AND MOORA METHODS IN ESTIMATION OF THE SAFETY OF COUNTRIES JF - JOURNAL OF LIFE ECONOMICS JA - JLECON VL - 7 IS - 2 SE - Research Articles DO - 10.15637/jlecon.7.008 UR - https://journals.gen.tr/index.php/jlecon/article/view/1035 SP - 123-134 AB - <p><em>In recent years, because of the developments in software and hardware technology, the datasets used in research have expanded, and with the effects of artificial intelligence technologies, the models used in forecasts have enabled to obtain results with broader meanings. In this study, using the crime index calculated to reveal the crime rates in the countries every year, the safety positions of the 106 countries was estimated. For this purpose, logistic regression analysis, artificial neural networks and MOORA method, which is one of the multi-criteria decision making methods and also not a classification method, has been used to provide a different point of view. As a result of the study, it is determined that the correct classification rate of estimations made according to the safety of countries with artificial neural networks method is higher than other methods.</em></p> ER -