dc.creator | Nieto-Chaupis, Huber | |
dc.date.accessioned | 2023-12-28T14:22:20Z | |
dc.date.accessioned | 2024-08-06T20:55:59Z | |
dc.date.available | 2023-12-28T14:22:20Z | |
dc.date.available | 2024-08-06T20:55:59Z | |
dc.date.created | 2023-12-28T14:22:20Z | |
dc.date.issued | 2023 | |
dc.identifier | https://hdl.handle.net/20.500.13067/2922 | |
dc.identifier | Intelligent Systems and Applications | |
dc.identifier | https://doi.org/10.1007/978-3-031-16072-1_37 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/9538962 | |
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. | |
dc.language | eng | |
dc.publisher | Springer Link | |
dc.relation | https://link.springer.com/chapter/10.1007/978-3-031-16072-1_37 | |
dc.rights | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.rights | info:eu-repo/semantics/restrictedAccess | |
dc.subject | COVID-19 | |
dc.subject | Shanon’s entropy | |
dc.subject | Geometry modeling | |
dc.title | Entropy of Shannon from Geometrical Modeling of Covid-19 Infections Data: The Cases of USA and India | |
dc.type | info:eu-repo/semantics/article | |