dc.creatorNieto-Chaupis, Huber
dc.date.accessioned2023-12-28T14:22:20Z
dc.date.accessioned2024-08-06T20:55:59Z
dc.date.available2023-12-28T14:22:20Z
dc.date.available2024-08-06T20:55:59Z
dc.date.created2023-12-28T14:22:20Z
dc.date.issued2023
dc.identifierhttps://hdl.handle.net/20.500.13067/2922
dc.identifierIntelligent Systems and Applications
dc.identifierhttps://doi.org/10.1007/978-3-031-16072-1_37
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9538962
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.
dc.languageeng
dc.publisherSpringer Link
dc.relationhttps://link.springer.com/chapter/10.1007/978-3-031-16072-1_37
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectCOVID-19
dc.subjectShanon’s entropy
dc.subjectGeometry modeling
dc.titleEntropy of Shannon from Geometrical Modeling of Covid-19 Infections Data: The Cases of USA and India
dc.typeinfo:eu-repo/semantics/article


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