As a complex
geospatial structure, Turkish national highway transportation network is
studied by the means of network science. We used the dataset retrieved from the
KGM (Karayolları Genel Müdürlüğü) maps with a hand-driven process. The dataset
labels the junctions in the map as nodes, and the roads between these junctions
as edges. We outlined the statistical properties of the Turkish highway
transportation network by the means of eigenvector, betweenness, closeness
centrality, modularity and eccentricity measures, while comparative percentile
plots between these measures are also performed. We investigated the
correlation of these parameters with the traffic volume, and outlined that only
eccentricity measure is correlated with the traffic volume. We also
investigated the degree correlations of the network and found that the network
displays disassortative mixing behavior, meaning that nodes with high degrees
tend to connect with lower degree nodes, and vice versa. This property is
consistent with the recent studies of transportation networks, as well as
various types of real networks like Internet, World-Wide Web, protein interactions,
neural network etc.
Journal Section | Araştırma Articlessi |
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Authors | |
Publication Date | February 15, 2018 |
Published in Issue | Year 2018 Volume: 6 Issue: 1 |
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