20.500.12556/RUL-154272 Analiza prometnih omrežij z uporabo računskih pristopov za analizo presnovnih omrežij Analysis of traffic networks with the application of computational approaches for the analysis of metabolic networks Prometna omrežja večjih mest postajajo vedno bolj zasičena, saj večina ljudi dela v mestih, živi pa nekje na obrobju. Poleg tega se v zahodnem svetu vsako leto število avtomobilov na prebivalca povečuje. Posledica tega je večje število prometnih zastojev, ki povzročajo daljše čase potovanja, večjo porabo goriva in poslabšanje kakovosti zraka. Z analiziranjem prometnih omrežij pridobimo ključne informacije o kritičnih delih omrežja, ki se lahko nato z urbanim planiranjem izboljšajo. Prometna omrežja lahko primerjamo s presnovnimi omrežji, saj pri obeh govorimo o kompleksnih dinamičnih sistemih, v katerih nas predvsem zanima pretok skozi omrežje. Glavni cilj diplomske naloge je preučiti uporabo pristopov za analizo presnovnih omrežij na analizi prometnih omrežij. Pri tem smo se naslonili na programske pakete OSMnx ter COBRApy v jeziku Python. COBRApy je programski paket, namenjen predvsem modeliranju in analizi presnovnih omrežij. Zaradi podobnosti med biološkimi in prometnimi omrežji smo ga prilagojeno uporabili pri analizi prometnih omrežij. Podatke o prometnem omrežju smo pridobili preko paketa OSMnx, ki predstavlja vmesnik do podatkov spletnega zemljevida OpenStreetMap. Na našem prometnem modelu smo uporabili algoritme za analizo presnovnih omrežij, ki ponujajo možnost izvajanja obsežnega niza analiz, kot so ocenjevanje prometnega pretoka skozi mesto, identifikacija ključnih odsekov cest ipd. Tak pristop nudi avtomatizirano ogrodje za vzpostavitev in analizo modelov velikih prometnih omrežij. Traffic networks of major cities are becoming increasingly congested as the majority of people work in cities while living on the outskirts. Furthermore, in the Western world, the number of cars per capita increases every year. The consequence of this is a higher number of traffic jams, leading to longer travel times, increased fuel consumption, and worsened air quality. By analyzing traffic networks, we obtain key information about critical parts of the network, which can then be improved through urban planning. Traffic networks can be compared to metabolic networks, as both are complex dynamic systems with flow as a key parameter. The main objective of this thesis is to examine the application of approaches for analyzing metabolic networks in the analysis of traffic networks. We relied on Python packages OSMnx and COBRApy for this purpose. COBRApy is a software package primarily designed for modelling and analyzing metabolic networks, but due to the similarities between biological and traffic networks, we adapted it for traffic network analysis. We obtained traffic network data through the OSMnx package, which serves as an interface to OpenStreetMap data. In our traffic model, we used algorithms for the analysis of metabolic networks, offering the possibility of conducting an extensive range of analyses, such as evaluating traffic flow through the city, identifying key road segments, etc. This approach provides a fully automated framework for establishing and analyzing models of large traffic networks. modeliranje prometnih omrežij OSMnx COBRApy modeliranje na osnovi omejitev traffic modelling OSMnx COBRApy constrained based modelling true false false Slovenski jezik Angleški jezik Diplomsko delo/naloga 2024-02-05 11:10:13 2024-02-05 11:10:22 2024-02-09 06:52:25 0000-00-00 00:00:00 2024 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 36551 184557827 Marolt_Nika_-_Analiza_prometnih_omrezij_z_uporabo_racunskih_pristopov_za_analizo_presnovnih_omre.pdf Marolt_Nika_-_Analiza_prometnih_omrezij_z_uporabo_racunskih_pristopov_za_analizo_presnovnih_omre.pdf 1 138960E3BBB3599743D1C04CAB469745 f0ff27d8eaf18050ca009c17362dad904f149e258d5b11098f820806256c6b8e c7dbbb38-c40e-11ee-8e16-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=180569 Fakulteta za računalništvo in informatiko 0 0 0