Theoretical Artificial Intelligence Based on Shannon Entropy to Identify Strains in Covid-19 Pandemic

dc.creatorNieto-Chaupis, Huber
dc.date.accessioned2022-04-29T20:50:29Z
dc.date.accessioned2023-05-30T23:14:06Z
dc.date.available2022-04-29T20:50:29Z
dc.date.available2023-05-30T23:14:06Z
dc.date.created2022-04-29T20:50:29Z
dc.date.issued2021-10-18
dc.identifierNieto-Chaupis, H. (2021). Theoretical Artificial Intelligence Based on Shannon Entropy to Identify Strains in Covid-19 Pandemic. In 2021 Third International Conference on Transdisciplinary AI (TransAI) (pp. 45-46). IEEE.
dc.identifier978-1-6654-3412-6
dc.identifierhttps://hdl.handle.net/20.500.13067/1817
dc.identifier2021 Third International Conference on Transdisciplinary AI (TransAI)
dc.identifierhttps://doi.org/10.1109/TransAI51903.2021.00016
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/6474009
dc.description.abstractBased in the fact that ongoing pandemic is caused by a kind of disorder, this paper employs the concept of Shannon entropy to model data of infections by Covid-19. The usage of this represents a proposal as a type of artificial intelligence that might be used in advanced softwares to perform instantaneous measurements of new infections. The presented theory is applied to the case of UK data, yielding an interesting matching. Therefore, it is seen that waves of pandemics can be explained in terms of apparition of strains and entropy.
dc.languageeng
dc.publisherUniversidad Autónoma del Perú
dc.publisherPE
dc.relationhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85125747960&doi=10.1109%2fTransAI51903.2021.00016&partnerID=40
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceAUTONOMA
dc.source45
dc.source46
dc.subjectCOVID-19
dc.subjectCorrelation
dc.subjectPandemics
dc.subjectEntropy
dc.subjectSoftware
dc.subjectData models
dc.subjectProposals
dc.titleTheoretical Artificial Intelligence Based on Shannon Entropy to Identify Strains in Covid-19 Pandemic
dc.typeinfo:eu-repo/semantics/article


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