Cargando…
A quantitative analysis of the impact of explicit incorporation of recency, seasonality and model specialization into fine-grained tourism demand prediction models
Forecasting is of utmost importance for the Tourism Industry. The development of models to predict visitation demand to specific places is essential to formulate adequate tourism development plans and policies. Yet, only a handful of models deal with the hard problem of fine-grained (per attraction)...
Autores principales: | Khatibi, Amir, Couto da Silva, Ana Paula, Almeida, Jussara M., Gonçalves, Marcos A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9731488/ https://www.ncbi.nlm.nih.gov/pubmed/36480566 http://dx.doi.org/10.1371/journal.pone.0278112 |
Ejemplares similares
-
Correction: A quantitative analysis of the impact of explicit incorporation of recency, seasonality and model specialization into fine-grained tourism demand prediction models
Publicado: (2023) -
FISETIO: A FIne-grained, Structured and Enriched Tourism Dataset for Indoor and Outdoor attractions
por: Khatibi, Amir, et al.
Publicado: (2019) -
ARMAX modelling of international tourism demand
por: Lim, Christine, et al.
Publicado: (2009) -
Long-Term Recency in Anterograde Amnesia
por: Talmi, Deborah, et al.
Publicado: (2015) -
The HIV Genomic Incidence Assay Meets False Recency Rate and Mean Duration of Recency Infection Performance Standards
por: Park, Sung Yong, et al.
Publicado: (2017)