Transferability of a Machine Learning-Based Model of Hourly Traffic Volume Estimation—Florida and New Hampshire Case Study
This paper focuses on the problem of model transferability for machine learning models used to estimate hourly traffic volumes. The presented findings enable not only an increase in the accuracy of existing models but also, simultaneously, reduce the cost of data needed for training the models—makin...
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Main Authors: | Przemysław Sekuła, Zachary Vander Laan, Kaveh Farokhi Sadabadi, Krzysztof Kania, Sara Zahedian |
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Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
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Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2021/9944918 |
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