ÜLKELERİN GÜVENLİ OLMALARININ TAHMİNİNDE LOJİSTİK REGRESYON, YAPAY SİNİR AĞLARI VE MOORA YÖNTEMLERİNİN KARŞILAŞTIRILMASI

Ozlem DENİZ BAŞAR; Elif GÜNEREN GENÇ

doi:10.15637/jlecon.7.008

Authors

Ozlem DENİZ BAŞAR Istanbul Commerce University/TURKEY
Elif GÜNEREN GENÇ Istanbul Commerce University/TURKEY

10.15637/jlecon.7.008

Abstract

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.

Keywords:

Artificial Neural Network Logistic Regression Analysis MOORA Safety Classification

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