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102. Models for forecasting the traffic flow within the city of LjubljanaGašper Petelin, Rok Hribar, Gregor Papa, 2023, izvirni znanstveni članek Povzetek: Efficient traffic management is essential in modern urban areas. The development of intelligent traffic flow prediction systems can help to reduce travel times and maximize road capacity utilization. However, accurately modeling complex spatiotemporal dependencies can be a difficult task, especially when real-time data collection is not possible. This study aims to tackle this challenge by proposing a solution that incorporates extensive feature engineering to combine historical traffic patterns with covariates such as weather data and public holidays. The proposed approach is assessed using a new real-world data set of traffic patterns collected in Ljubljana, Slovenia. The constructed models are evaluated for their accuracy and hyperparameter sensitivity, providing insights into their performance. By providing practical solutions for real-world scenarios, the proposed approach offers an effective means to improve traffic flow prediction without relying on real-time data.
Ključne besede: traffic modeling, time-series forecasting, traffic-count data set, machine learning, model comparison
Objavljeno v DiRROS: 28.09.2023; Ogledov: 407; Prenosov: 166
 Celotno besedilo (5,05 MB)
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106. Single-layer and double-layer filtration materials based on polyvinylidene fluoride-co-hexafluoropropylene nanofibers coated on melamine microfibersTilen Potisk, Maja Remškar, Luka Pirker, Gregor Filipič, Igor Mihelič, Marjan Ješelnik, Urban Čoko, Miha Ravnik, 2023, izvirni znanstveni članek Ključne besede: nanofibers, aerosols, filtration
Objavljeno v DiRROS: 15.09.2023; Ogledov: 322; Prenosov: 172
Celotno besedilo (2,07 MB)
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