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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Vydané v:	IEEE open journal of intelligent transportation systems Ročník 4; s. 740 - 754
Hlavní autori:	Agriesti, Serio, Kuzmanovski, Vladimir, Hollmen, Jaakko, Roncoli, Claudio, Nahmias-Biran, Bat-Hen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Activity-based transport modeling Algorithms Bayes methods Bayesian analysis Bayesian optimization Behavioral sciences Calibration Complexity Computational modeling Data models machine learning model calibration Optimization Parameters surrogate model Transportation Transportation models
ISSN:	2687-7813, 2687-7813
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