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Tourism demand forecasting of multi-attractions with spatiotemporal grid: a convolutional block attention module model
Effective tourist demand forecasting is crucial for company operations and destination management. Furthermore, tourists may plan better personalized multi-attraction itineraries based on demand forecasting to avoid travel peaks and improve the enjoyment of their vacation. This study developed a uni...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10075180/ http://dx.doi.org/10.1007/s40558-023-00247-y |