Nalazite se na CroRIS probnoj okolini. Ovdje evidentirani podaci neće biti pohranjeni u Informacijskom sustavu znanosti RH. Ako je ovo greška, CroRIS produkcijskoj okolini moguće je pristupi putem poveznice www.croris.hr
izvor podataka: crosbi !

Forecasting transport mode use with support vector machines based approach (CROSBI ID 239349)

Prilog u časopisu | izvorni znanstveni rad

Semanjski, Ivana ; Lopez Aguirre, Angel Javier ; Gautama, Sidharta Forecasting transport mode use with support vector machines based approach // Transactions on maritime science, 5 (2016), 2; 111-120

Podaci o odgovornosti

Semanjski, Ivana ; Lopez Aguirre, Angel Javier ; Gautama, Sidharta

engleski

Forecasting transport mode use with support vector machines based approach

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.

GNSS, Transport mode, Crowdsourceing, Travel behavior, Smart city, Forecasting, Pre-travel information service, Support vector machines, Smartphones

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

Podaci o izdanju

5 (2)

2016.

111-120

objavljeno

1848-3305

1848-3313

Povezanost rada

Tehnologija prometa i transport