Pregled bibliografske jedinice broj: 1148053
Classification of Travel Modes from Cellular Network Data Using Machine Learning Algorithms
Classification of Travel Modes from Cellular Network Data Using Machine Learning Algorithms // Proceedings of ELMAR-2021 / Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka (ur.).
Zadar: Sveučilište u Zagrebu, 2021. str. 173-177 doi:10.1109/ELMAR52657.2021.9550817 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Classification of Travel Modes from Cellular Network Data Using Machine Learning Algorithms
Autori
Tišljarić, Leo ; Cvetek, Dominik ; Vareškić, Valentin ; Gregurić, Martin
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of ELMAR-2021
/ Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka - Zadar : Sveučilište u Zagrebu, 2021, 173-177
ISBN
978-1-6654-4436-1
Skup
63rd International Symposium ELMAR-2021
Mjesto i datum
Zadar, Hrvatska, 13.09.2021. - 15.09.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Travel mode classification ; Machine learning ; Cellular network data ; Origin-destination matrices
Sažetak
Data availability in recent years has grown exponentially, allowing researchers in the transport sector to harness valuable information regarding traffic flows. In that sense, cellular network data represents valuable traffic information when dealing with spatially large areas due to its property of collecting route data using distant mobile base stations. This property enables the automatic collection of origin-destination data, which is traditionally collected using field or online questionnaires. This paper aims to present the possibility of using origin-destination data extracted from cellular network dataset to classify travel modes. A case study was performed on the dataset collected in the City of Rijeka, Croatia. Dataset is evaluated on five machine learning algorithms, which resulted in Random forest as the highest performing algorithm with an accuracy score of 99.93%
Izvorni jezik
Engleski
Znanstvena područja
Tehnologija prometa i transport, Interdisciplinarne tehničke znanosti, Informacijske i komunikacijske znanosti, Interdisciplinarne društvene znanosti
POVEZANOST RADA
Projekti:
--KK.01.1.1.01.009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Šmuc, Tomislav; Lončarić, Sven; Petrović, Ivan; Jokić, Andrej; Palunko, Ivana) ( CroRIS)
Ustanove:
Fakultet prometnih znanosti, Zagreb
Profili:
Martin Gregurić
(autor)
Valentin Vareškić
(autor)
Leo Tišljarić
(autor)
Dominik Cvetek
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Conference Proceedings Citation Index - Science (CPCI-S)
- Scopus