Pregled bibliografske jedinice broj: 876227
Forecasting transport mode use with support vector machines based approach
Forecasting transport mode use with support vector machines based approach // Transactions on maritime science, 5 (2016), 2; 111-120 (podatak o recenziji nije dostupan, članak, znanstveni)
CROSBI ID: 876227 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Forecasting transport mode use with support vector machines based approach
Autori
Semanjski, Ivana ; Lopez Aguirre, Angel Javier ; Gautama, Sidharta
Izvornik
Transactions on maritime science (1848-3305) 5
(2016), 2;
111-120
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
GNSS ; Transport mode ; Crowdsourceing ; Travel behavior ; Smart city ; Forecasting ; Pre-travel information service ; Support vector machines ; Smartphones
(GNSS, Transport mode, Crowdsourceing, Travel behavior, Smart city, Forecasting, Pre-travel information service, Support vector machines, Smartphones)
Sažetak
The paper explores potential to forecast what transport mode one will use for his/her next trip. The support vector machines based approach learns from individual's behavior (validated GPS tracks) to support smart city transport planning services. The overall success rate, in forecasting the transport mode, is 82 %, with lower confusion for private car, bike and walking.
Izvorni jezik
Engleski
Znanstvena područja
Tehnologija prometa i transport
Citiraj ovu publikaciju:
Uključenost u ostale bibliografske baze podataka::
- Transportation Research Information Services - TRIS
