ANN-Based traffic volume prediction models in response to COVID-19 imposed measures.

Ghanim, Mohammad Shareef; Muley, Deepti; Kharbeche, Mohamed

Ghanim, Mohammad Shareef; Muley, Deepti; Kharbeche, Mohamed.

Afiliación

Ghanim MS; Ministry of Transport and Communications, P.O. Box 224455, Doha, Qatar.
Muley D; Qatar Transportation and Traffic Safety Center, Department of Civil Engineering, Qatar University, P.O. Box 2713, Doha, Qatar.
Kharbeche M; Qatar Transportation and Traffic Safety Center, Qatar University, P.O. Box 2713, Doha, Qatar.

Sustain Cities Soc ; 81: 103830, 2022 Jun.

Article en En | MEDLINE | ID: mdl-35291578

Palabras clave

COVID-19; Machine Learning; Mobility Impact; Pandemic Preventive Measures; Prediction Model; State of Qatar; Traffic Mobility

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sustain Cities Soc Año: 2022 Tipo del documento: Article País de afiliación: Qatar Pais de publicación: Países Bajos

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