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

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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Bibliographic Details
Main Authors: Serio Agriesti, Vladimir Kuzmanovski, Jaakko Hollmen, Claudio Roncoli, Bat-Hen Nahmias-Biran
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of Intelligent Transportation Systems
Subjects:
Activity-based transport modeling
model calibration
machine learning
Bayesian optimization
surrogate model
Online Access:https://ieeexplore.ieee.org/document/10268587/

Internet

https://ieeexplore.ieee.org/document/10268587/

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