International Conference on Eurasian Economies
9-11 September 2015 – Kazan, RUSSIA
Paper detail
Paper ID : 1253
Status : Paper published
Language : Turkish
Topic : Regional Economics
Presenter: Asst. Prof. Dr. Necati Alp Erilli
Session : 6B Bölgesel Ekonomiler II
Classification of Turkish Republics with Specific Economic Indicators in Fuzzy Clustering Analysis
Türk Cumhuriyetlerinin Bulanık Kümeleme Analizi ile Belirlenen Ekonomik Göstergelerle Sınıflandırılması
- Asst. Prof. Dr. Necati Alp Erilli (Cumhuriyet University, Türkiye)
- Asst. Prof. Dr. Çağatay Karaköy (Cumhuriyet University, Türkiye)
Abstract
Economic indicators in economic policies have an important place in determining the levels of development. Determining and classifying the existing social and economic structures of countries is very important for examining the development states and possible development tendencies of countries and forming regional development policies in line with these. The aim in cluster analysis, is to classify datas in to similarity and perform useful knowledge for the researcher. Cluster analysis, which became more popular among the subjects of statistical classification in recent years, can give more reliable results when there is apriori knowledge about number of clusters. Fuzzy models interested in fuzzy model structures and try to estimate system behaviours that has no knowledge about their structure. Fuzzy Cluster Analysis is try to decompose the groups which membership degrees cannot be determined. When the number of datas and variables increased or cluster structures came to closer for all, Cluster analysis has given more successful results then the other cluster analysis methods. In this study, Turkish Republics were classified in terms of the indicators determined by using Fuzzy C-Means (FCM) and Gath Geva methods which are frequently used in fuzzy clustering analysis. The objective was to find out the common class structures of Turkish Republics which came out with the disintegration of the Soviet Union in 1991 and which experienced economic similar problems and thus to help countries in the same clusters in similar economic planning. Results are also compared between fuzzy and crisp clustering analysis methods.
JEL codes: C38
Erilli, Necati Alp, Karaköy, Çağatay (2015). "Classification of Turkish Republics with Specific Economic Indicators in Fuzzy Clustering Analysis" in Proceedings of International Conference of Eurasian Economies 2015, pp.305-310, Kazan, RUSSIA.
DOI: https://doi.org/10.36880/C06.01253
Session 6B: Bölgesel Ekonomiler II
