Predicting travel mode choice with a robust neural network and Shapley additive explanations analysis
Abstract Predicting and understanding travellers’ mode choices is crucial to developing urban transportation systems and formulating traffic demand management strategies. Machine learning (ML) methods have been widely used as promising alternatives to traditional discrete choice models owing to thei...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Wiley
2024-07-01
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| Series: | IET Intelligent Transport Systems |
| Assuntos: | |
| Acceso en liña: | https://doi.org/10.1049/itr2.12514 |
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