- author = "Matej Babic and Cristiano Fragassa and Dragan Marinkovic and Janez Povh",
- title = "Machine Learning Tools in the Analyze of a Bike Sharing",
- journal = "International Journal for Quality Research",
- year = "2022",
- volume = "16",
- number = "2",
- pages = "375--394",
- keywords = "genetic algorithms, genetic programming, GoNM, Transportation Systems Engineering, bicycle, Cycles, Bike-Sharing System (PBS), Artificial Intelligence (AI), Machine Learning (ML), Hybrid Intelligent Systems, Weather Conditions",
- ISSN = "1800-6450",
-
URL = "
http://ijqr.net/paper.php?id=989",
-
URL = "
http://ijqr.net/journal/v16-n2/4.pdf",
-
DOI = "
doi:10.24874/IJQR16.02-04",
- size = "20 pages",
- abstract = "Advanced models, based on artificial intelligence and machine learning, are used here to analyze a bike-sharing system. The specific target was to predict the number of rented bikes in the Nova Mesto, Slovenia public bike share scheme. For this purpose, the topological properties of the transport network were determined and related to the weather conditions. Pajek software was used and the system behavior during a 30-week period was investigated. Open questions were, for instance: how many bikes are shared in different weather conditions? How the network topology impacts the bike sharing system? By providing a reasonable answer to these and similar questions, several accurate ways of modeling the bike sharing system which account for both topological properties and weather conditions, were developed and used for its optimization.",
-
notes = "02.06.2021 seminar:
https://www.fpp.uni-lj.si/en/research/kappra-coffee-talks-on-research/2022053112194477/kappra-no-24
http://ijqr.net/",
