RECLASSIFICATION OF COUNTRIES ACCORDING TO HUMAN DEVELOPMENT INDEX: AN APPLICATION WITH ANN AND ANFIS METHODS

Classification problems are frequently encountered in the fields of statistics, econometrics and data mining. Techniques used to solve the problem are changing and developing day by day depending on the technology of the age. For this purpose, besides multivariate statistical techniques, methods based on fuzzy and artificial intelligence are also used today. This study aims to make a comparison between the classification performances of artificial neural network (ANN) from machine learning techniques and Adaptive Neural Fuzzy Inference System (ANFIS), which is a combination of ANN and fuzzy logic technique and is based on hybrid learning technique. For this purpose, the countries were classified according to the Human Development Index (HDI) and ANN and ANFIS methods and the results were compared with the HDI. In this context, the HDI of 2015 was measured for 185 countries by using 27 development indicators under eight main topics of health, entrepreneurship, macroeconomics and microeconomics, logistics, trade, social life and natural factors and classification of these countries was estimated. When the analysis results are considered, in economic terms, development is composed of seven factors and eight main subjects according to the estimated index calculated in the study, which is different from the HDI. In terms of statistics, countries have been classified correctly at a rate of 87.5% according to ANN and 91.36% according to ANFIS. In this case, it was observed that the ANFIS method gave better results than ANN.

ÜLKELERİN İNSANİ GELİŞMİŞLİK ENDEKSİNE GÖRE YENİDEN SINIFLANDIRILMASI: YAPAY SİNİR AĞI VE ANFIS YÖNTEMLERİ İLE BİR UYGULAMA

İstatistik, ekonometri ve veri madenciliği alanlarında sınıflandırma problemlerine sıklıkla karşılaşılmaktadır. Bu amaç doğrultusunda kullanılan yöntemler teknolojiye bağlı olarak günden güne değişmekte ve gelişmektedir. Bu kapsamda çok değişkenli istatistik ve yapay zeka yöntemleri günümüzde kullanılmaktadır. Bu çalışmada, makine öğrenme tekniklerinden yapay sinir ağı (ANN) ve YSA ile bulanık mantık tekniğinin birleşimi olan ve hibrid öğrenme tekniğine dayanan Adaptif Ağ Tabanlı Bulanık Çıkarım Sistemi (Adaptive Neural Fuzzy Inference System-ANFIS) yöntemlerinin sınıflandırma performanslarının karşılaştırılması amaçlanmaktadır. Bu amaç doğrultusunda Birleşmiş Milletler Dünya Gelişmişlik Göstergeleri ve ANN ve ANFIS yöntemleri kullanılarak İnsani Gelişmişlik Endeksi’ne (HDI) göre ülkeler sınıflandırılmış ve elde edilen sonuçlar İGE ile karşılaştırılmıştır. Analiz sonuçları ele alındığında, iktisadi açıdan; çalışmada hesaplanan tahmini endekse göre gelişmişlik, İGE’den farklı olarak, yedi faktör ve sekiz ana konudan oluşmaktadır. İstatistiki açıdan ülkeler; ANN’ye göre %87.5 ve ANFIS’e göre %91.36 oranında doğru sınıflandırılmıştır. Bu durumda ANFIS yönteminin ANN’den daha başarılı sonuçlar verdiği gözlenmiştir.

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Business and Management Studies: An International Journal-Cover
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  • Başlangıç: 2013
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