AIR TRAFFIC ANALYSIS OF COUNTRIES WITH RENYI ENTROPY

Abstract

Centrality is one of the most frequently studied subjects of social network analysis. The identification of the most effective entities in a network or system can be found by measures of centrality. In this study, using the data of air traffic with Renyi entropy, the most influential countries in this field were analyzed in the graph structure. The most effective countries in air traffic were identified. It has been shown that centrality measurements can be made with Renyi entropy in a weighted and directional network. A method for the detection of vital nodes in a network was proposed. Difference from Shannon, it was observed that results could be obtained for different situations by using the α coefficient in Renyi. Sometimes measuring only the effect of edge weight or node degree does not yield accurate results. Using α to adjust this effect has enabled us to get more accurate results.

Keywords

• Air Traffic,Complex Networks,Graphs,Renyi Entropy,Node Centrality

RENYI ENTROPI ILE ÜLKELERİN HAVA TRAFİĞİNİN ANALİZİ

Abstract

Merkezilik sosyal ağ analizi yapan kişilerin en çok çalıştığı konulardan biridir. Bir ağdaki en etkili ve sisteme etkisi olan varlıkların tespiti merkezilik ölçüleri ile bulunabilir. Bu çalışmada Renyi entropi ile havayolu trafiği verileri kullanılarak bu alandaki en etkili ülkeler çizge yapısında analiz edildi. Hava trafiğinde en merkezi ülkeler tespit edildi. Ağırlıklı ve yönlü bir ağda Renyi entropi ile merkezilik ölçümlerinin yapılabileceği gösterildi. Bir ağdaki hayati öneme sahip düğümlerin tespiti için bir yöntem önerildi. Shannon’dan farklı olarak Renyi’de α katsayısı kullanılarak farklı durumlar için sonuç elde edilebileceği görüldü. Sadece kenar ağırlıklarının veya düğüm derecelerinin etkisinin ölçülmesi bazen doğru sonuçlar vermediği için α’nın bu etkiyi ayarlamak için kullanılması daha doğru sonuçlar almamızı sağladı.

Keywords

• Havayolu,Kompleks Ağlar,Çizgeler,Renyi Entropi,Düğüm Merkeziliği

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