Machine learning approach versus probabilistic approach to model the departure time of non-mandatory trips-Reference-Cited by-同舟云学术

Machine learning approach versus probabilistic approach to model the departure time of non-mandatory trips

Published:2022-01 Issue: Volume:586 Page:126492
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Rasaizadi Arash^ORCID,Farzin Iman,Hafizi Fateme

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistics and Probability

Reference42 articles.

1. A copula-based joint model to capture the interaction between mode and departure time choices in urban trips;Seyedabrishami;Transp. Res. Procedia,2019

2. The interaction between activity choice and duration: Application of copula-based and nested-logit models;Jafari Shahdani;Sci. Iran.,2020

3. Consideration of both latent variables and taste variation in modeling destination choice for student’s non-mandatory activities;Yaghoubi;Int. J. Civ. Eng.,2020

4. Regret minimization based joint econometric model of mode choice and departure time: a case study of university students in Toronto, Canada;Anowar;Transp. A: Trans. Sci.,2019

5. Joint discrete-continuous model of travel mode and departure time choices;Shabanpour;Transp. Res. Rec.,2017

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