Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
This paper proposes a pattern recognition model to develop clusters of homogenous activities for blue-collar workers in the State of Qatar. The activity-based data from the travel diary of 1051 blue-collar workers collected by the Ministry of Transportation and Communication (MoTC) in Qatar was used...
Guardado en:
Autores principales: | Aya Hasan Alkhereibi, Shahram Tahmasseby, Semira Mohammed, Deepti Muley |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/d6eaea27e6b84cdeab7c61f8a5e8d0ad |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Structural equation modeling of public transport use with COVID-19 precautions: An extension of the norm activation model
por: Muhammad Ashraf Javid, et al.
Publicado: (2021) -
Truck travel time performance measures and their association with on- and off-network characteristics
por: Sarvani Duvvuri, et al.
Publicado: (2021) -
Post COVID-19 teleworking and car use intentions. Evidence from large scale GPS-tracking and survey data in the Netherlands
por: Marie-José Olde Kalter, et al.
Publicado: (2021) -
Multitasking onboard of conventional transport modes and shared autonomous vehicles
por: Jamil Hamadneh, et al.
Publicado: (2021) - Travel holiday