Türker, I.2024-09-292024-09-292018https://doi.org/10.17694/bajece.369235https://search.trdizin.gov.tr/tr/yayin/detay/292107https://hdl.handle.net/20.500.14619/10403As a complex geospatial structure, Turkish nationalhighway transportation network is studied by the means ofnetwork 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 roadsbetween these junctions as edges. We outlined the statisticalproperties of the Turkish highway transportation network by themeans of eigenvector, betweenness, closeness centrality,modularity and eccentricity measures, while comparativepercentile plots between these measures are also performed. Weinvestigated the correlation of these parameters with the trafficvolume, and outlined that only eccentricity measure is correlatedwith the traffic volume. We also investigated the degreecorrelations of the network and found that the network displaysdisassortative mixing behavior, meaning that nodes with highdegrees tend to connect with lower degree nodes, and vice versa.This property is consistent with the recent studies oftransportation networks, as well as various types of real networkslike Internet, World-Wide Web, protein interactions, neuralnetwork etc.eninfo:eu-repo/semantics/openAccessMühendislikBiyotıpMühendislikElektrik ve ElektronikBilgisayar BilimleriYazılım MühendisliğiYeşilSürdürülebilir Bilim ve TeknolojiTelekomünikasyonBilgisayar BilimleriSibernitikBilgisayar BilimleriBilgi SistemleriBilgisayar BilimleriDonanım ve MimariBilgisayar BilimleriTeori ve MetotlarBilgisayar BilimleriYapay ZekaArticle10.17694/bajece.369235191132921076