dc.contributor.author | Nieto-Chaupis, Huber | |
dc.date.accessioned | 2023-12-28T14:22:20Z | |
dc.date.available | 2023-12-28T14:22:20Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://hdl.handle.net/20.500.13067/2922 | |
dc.description.abstract | Between 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.format | application/pdf | es_PE |
dc.language.iso | eng | es_PE |
dc.publisher | Springer Link | es_PE |
dc.rights | info:eu-repo/semantics/restrictedAccess | es_PE |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | es_PE |
dc.subject | COVID-19 | es_PE |
dc.subject | Shanon’s entropy | es_PE |
dc.subject | Geometry modeling | es_PE |
dc.title | Entropy of Shannon from Geometrical Modeling of Covid-19 Infections Data: The Cases of USA and India | es_PE |
dc.type | info:eu-repo/semantics/article | es_PE |
dc.identifier.journal | Intelligent Systems and Applications | es_PE |
dc.identifier.doi | https://doi.org/10.1007/978-3-031-16072-1_37 | |
dc.subject.ocde | https://purl.org/pe-repo/ocde/ford#2.02.04 | es_PE |
dc.relation.url | https://link.springer.com/chapter/10.1007/978-3-031-16072-1_37 | es_PE |