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COVID-19: Metaheuristic Optimization-Based Forecast Method on Time-Dependent Bootstrapped Data

dc.contributor.authorFenga, L
dc.contributor.authorDel Castello, C
dc.date.accessioned2022-05-17T08:32:49Z
dc.date.issued2021-02-11
dc.date.updated2022-05-16T17:15:35Z
dc.description.abstractA compounded method—exploiting the searching capabilities of an operation research algorithm and the power of bootstrap techniques—is presented. The resulting algorithm has been successfully tested to predict the turning point reached by the epidemic curve followed by the COVID-19 virus in Italy. Future lines of research, which include the generalization of the method to a broad set of distribution, will be finally given.en_GB
dc.format.extent1-7
dc.identifier.citationVol. 2021, article 1235973en_GB
dc.identifier.doihttps://doi.org/10.1155/2021/1235973
dc.identifier.urihttp://hdl.handle.net/10871/129651
dc.identifierORCID: 0000-0002-8185-2680 (Fenga, Livio)
dc.language.isoenen_GB
dc.publisherHindawien_GB
dc.relation.urlhttps://github.com/pcm-dpc/COVID-19/tree/master/dati-regionien_GB
dc.rights© 2021 Livio Fenga and Carlo Del Castello. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_GB
dc.titleCOVID-19: Metaheuristic Optimization-Based Forecast Method on Time-Dependent Bootstrapped Dataen_GB
dc.typeArticleen_GB
dc.date.available2022-05-17T08:32:49Z
dc.identifier.issn1687-952X
dc.descriptionThis is the final version. Available from Hindawi via the DOI in this record. en_GB
dc.descriptionThe data used to support the findings of this study are publicly available, free of charge, at the web address https://github.com/pcm-dpc/COVID-19/tree/master/dati-regioni.en_GB
dc.identifier.eissn1687-9538
dc.identifier.journalJournal of Probability and Statisticsen_GB
dc.relation.ispartofJournal of Probability and Statistics, 2021
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2021-01-24
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2021-01-24
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-05-17T06:28:15Z
refterms.versionFCDVoR
refterms.dateFOA2022-05-17T08:32:56Z
refterms.panelCen_GB
refterms.depositExceptionpublishedGoldOA


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© 2021 Livio Fenga and Carlo Del Castello. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's licence is described as © 2021 Livio Fenga and Carlo Del Castello. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.