A COMPARISON OF LOGISTIC REGRESSION, ARTIFICIAL NEURAL NETWORKS AND MOORA METHODS IN ESTIMATION OF THE SAFETY OF COUNTRIES

Özlem DENİZ BAŞAR () and Elif GÜNEREN Gen㇠()
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Özlem DENİZ BAŞAR: İstanbul Ticaret University
Elif GÃœNEREN Genã‡: Ä°stanbul Ticaret University

JOURNAL OF LIFE ECONOMICS, 2020, vol. 7, issue 2, .123-134

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-criteriadecisionmakingmethods 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 (search for similar items in EconPapers)
JEL-codes: C24 C38 C44 C45 J28 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:jle:journl:v:7:y:2020:i:2:p:123-134

DOI: 10.15637/jlecon.7.008

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