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dc.contributor.authorRosser Limiñana, Pablo
dc.contributor.authorSoler, Seila
dc.date2024
dc.date.accessioned2024-07-04T08:57:57Z
dc.date.available2024-07-04T08:57:57Z
dc.identifier.citationPablo Rosser, Seila Soler. Enhancing Educational and Tourism Applications through Predictive Modeling of Cultural Heritage Site Visitation: use of Arima and autoregressive models, 21 June 2024, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-4515706/v1]es_ES
dc.identifier.issn2693-5015
dc.identifier.urihttps://reunir.unir.net/handle/123456789/16861
dc.description.abstractThis study focuses on the use of ARIMA and Autoregressive (AR) models to predict visitor flow to Civil War shelters in Alicante, highlighting seasonal patterns and differences among various visitor groups, with an enriching approach towards educational and tourism applications. Through a retrospective longitudinal design covering from August 2023 to January 2024, it analyzes the time series of visits, differentiating between the general public and school groups, as well as examining geographical demand. The research emphasizes the effectiveness and simplicity of the ARIMA(0, 0, 0) model with Logarithmic Transformation in modeling time series, while the AR(6) model proves indispensable for capturing short-term temporal dependencies. Despite the usefulness of these forecasts for future planning, the existence of uncertainties highlights the importance of adopting flexible management approaches and incorporating additional variables to refine predictions. This approach not only improves the management of visitor flows but also significantly contributes to the creation of more effective educational and tourism strategies, promoting the sustainability and appreciation of cultural heritage.es_ES
dc.language.isoenges_ES
dc.publisherResearch Squarees_ES
dc.relation.urihttps://www.researchsquare.com/article/rs-4515706/v1es_ES
dc.rightsopenAccesses_ES
dc.subjectcultural heritagees_ES
dc.subjectARIMA modelses_ES
dc.subjectautoregressivees_ES
dc.subjectvisitor predictiones_ES
dc.subjectAlicantees_ES
dc.titleEnhancing Educational and Tourism Applications through Predictive Modeling of Cultural Heritage Site Visitation: use of Arima and autoregressive modelses_ES
dc.typearticlees_ES
reunir.tag~OPUes_ES
dc.identifier.doihttps://doi.org/10.21203/rs.3.rs-4515706/v1


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