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BULANIK KÜMELEME ANALİZİ ile İSTATİSTİKİ BÖLGE BİRİMLERİNİN (İBBS) MALİ DEĞİŞKENLERE GÖRE SINIF LANDIRILMASI
2014
Journal:  
Kırıkkale University Journal of Social Sciences
Author:  
Abstract:

Abstract enEuropean Union has started works on keeping regional statistics to develop regional development politics as well as national development levels of member countries by dividing countries into sub regions. In line with these works, Turkey has been divided into three sub regions as Level 1 , Level 2 and Level 3 and regional statistics have begun to be collected and developed.Fuzzy Clustering approach comes out as a suitable method if the clusters are not seperated from each other prominently or if some of the members are indecisive about being a member of the cluster. Fuzzy clusters are functions that determine each unit between 0 and 1 defined as the membership of the unit. Units which are very similar take part in the same cluster according to high membership degree. The purpose here is to determine homogenous city groups that have the same characteristics in terms of these indicators.This study has used fuzzy c-means (FCM) method which is used frequently in fuzzy clustering analysis and has classified SCTU Level-2 and Level-3 regions through financial indicators. The results have been examined and interpreted in terms of their correlation with each other

Keywords:

The analysis of the statistics and statistics of the region (IBBS) according to the financial values
2014
Author:  
Abstract:

Abstract enEuropean Union has started works on keeping regional statistics to develop regional development politics as well as national development levels of member countries by dividing countries into subregions. In line with these works, Turkey has been divided into three subregions as Level 1 , Level 2 and Level 3 and regional statistics have begun to be collected and developed.Fuzzy Clustering approach comes out as a suitable method if the clusters are not separated from each other prominently or if some of the members are indecisive about being a member of the cluster. Fuzzy clusters are functions that determine each unit between 0 and 1 defined as the membership of the unit. Units which are very similar take part in the same cluster according to high membership degree. The purpose here is to determine homogenous city groups that have the same characteristics in terms of these indicators.This study has used fuzzy c-means (FCM) method which is used frequently in fuzzy clustering analysis and has classified SCTU Level-2 and Level-3 regions through financial indicators. The results have been examined and interpreted in terms of their correlation with each other

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Kırıkkale University Journal of Social Sciences

Field :   Sosyal, Beşeri ve İdari Bilimler

Journal Type :   Ulusal

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Article : 77
Cite : 24
Kırıkkale University Journal of Social Sciences