A Bayesian Optimization Approach for Calibrating Large-Scale Activity-Based Transport Models

Addressing complexity in transportation in cases such as disruptive trends or disaggregated management strategies has become increasingly important. This in turn is resulting in the rising adoption of Agent-Based and Activity-Based modeling. Still, a broad adoption is hindered by the high complexity...

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Principais autores:	Serio Agriesti, Vladimir Kuzmanovski, Jaakko Hollmen, Claudio Roncoli, Bat-Hen Nahmias-Biran
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2023-01-01
coleção:	IEEE Open Journal of Intelligent Transportation Systems
Assuntos:	Activity-based transport modeling model calibration machine learning Bayesian optimization surrogate model
Acesso em linha:	https://ieeexplore.ieee.org/document/10268587/
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