Enhanced tourist flow forecasting in Aosta Valley: A novel ensemble AI framework with adaptive temporal dynamics.
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| Title: | Enhanced tourist flow forecasting in Aosta Valley: A novel ensemble AI framework with adaptive temporal dynamics. |
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| Authors: | Alderighi M; Department of Economics, Management and Quantitative Methods, University of Milan, Milano, Italy., Ciano T; Department of Economics and Political Sciences, University of Aosta Valley, Aosta, Italy., Ferrara M; Department of Law, Economics and Human Sciences, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy., Santoro D; Department of Economics, Statistics and Business, Faculty of Technological and Innovation Sciences, Universitas Mercatorum, Roma, Italy. |
| Source: | PloS one [PLoS One] 2026 May 06; Vol. 21 (5), pp. e0336749. Date of Electronic Publication: 2026 May 06 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0336749 |
