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dc.contributor.authorNieto-Chaupis, Huber
dc.date.accessioned2023-12-28T14:22:20Z
dc.date.available2023-12-28T14:22:20Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/20.500.13067/2922
dc.description.abstractBetween the end of second semester of 2020 and along the first semester of 2021, Covid-19 has had a strong impact on United States and India as seen at the official statistics exhibiting a big number of new infections as well as fatalities, particularly India that have had sharp peaks at March 2021. The present paper addresses the question if there is a entropic nature in these cases from an intuitive model based at simple geometries that adjust well the histograms of new infections versus time. Although the geometry-based models might not be satisfactory in all, it provides a view that would lead to answer intrinsic questions related to the highest peaks of pandemic if these have a nature cause or are strongly related to disorder as dictated by Shannon’s entropy for instance.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherSpringer Linkes_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/es_PE
dc.subjectCOVID-19es_PE
dc.subjectShanon’s entropyes_PE
dc.subjectGeometry modelinges_PE
dc.titleEntropy of Shannon from Geometrical Modeling of Covid-19 Infections Data: The Cases of USA and Indiaes_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.journalIntelligent Systems and Applicationses_PE
dc.identifier.doihttps://doi.org/10.1007/978-3-031-16072-1_37
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.02.04es_PE
dc.relation.urlhttps://link.springer.com/chapter/10.1007/978-3-031-16072-1_37es_PE


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