A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem

Detalhes bibliográficos
Autor(a) principal: Benedito, Antone dos Santos [UNESP]
Data de Publicação: 2017
Outros Autores: Pio dos Santos, Fernando Luiz [UNESP], Rojas, I, Joya, G., Catala, A.
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/978-3-319-59153-7_10
http://hdl.handle.net/11449/164584
Resumo: In this paper, we describe a study of a parameter estimation technique to estimate a set of unknown biological parameters of a nonlinear dynamic model of dengue. We also explore a Levenberg-Marquardt (LM) algorithm to minimize the cost function. A classical mathematical model describes the dynamics of mosquitoes in water and winged phases, where the data are available. The main interest is to fit the model to the data taking into account the parameters estimated. Numerical simulations were performed and results showed the robustness of LM in estimating the important parameters in the dengue disease problem.
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spelling A Novel Technique to Estimate Biological Parameters in an Epidemiology ProblemComputational population dynamicsOrdinary differential systemAedesDengueIn this paper, we describe a study of a parameter estimation technique to estimate a set of unknown biological parameters of a nonlinear dynamic model of dengue. We also explore a Levenberg-Marquardt (LM) algorithm to minimize the cost function. A classical mathematical model describes the dynamics of mosquitoes in water and winged phases, where the data are available. The main interest is to fit the model to the data taking into account the parameters estimated. Numerical simulations were performed and results showed the robustness of LM in estimating the important parameters in the dengue disease problem.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Sao Paulo State Univ, Inst Biosci Botucatu, Botucatu, SP, BrazilSao Paulo State Univ, Inst Biosci Botucatu, Dept Biostat, BR-18618689 Botucatu, SP, BrazilSao Paulo State Univ, Inst Biosci Botucatu, Botucatu, SP, BrazilSao Paulo State Univ, Inst Biosci Botucatu, Dept Biostat, BR-18618689 Botucatu, SP, BrazilSpringerUniversidade Estadual Paulista (Unesp)Benedito, Antone dos Santos [UNESP]Pio dos Santos, Fernando Luiz [UNESP]Rojas, IJoya, G.Catala, A.2018-11-26T17:55:11Z2018-11-26T17:55:11Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject112-122application/pdfhttp://dx.doi.org/10.1007/978-3-319-59153-7_10Advances In Computational Intelligence, Iwann 2017, Pt I. Cham: Springer International Publishing Ag, v. 10305, p. 112-122, 2017.0302-9743http://hdl.handle.net/11449/16458410.1007/978-3-319-59153-7_10WOS:000443108200010WOS000443108200010.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAdvances In Computational Intelligence, Iwann 2017, Pt I0,295info:eu-repo/semantics/openAccess2023-09-30T06:01:22Zoai:repositorio.unesp.br:11449/164584Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:32:14.919650Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem
title A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem
spellingShingle A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem
Benedito, Antone dos Santos [UNESP]
Computational population dynamics
Ordinary differential system
Aedes
Dengue
title_short A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem
title_full A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem
title_fullStr A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem
title_full_unstemmed A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem
title_sort A Novel Technique to Estimate Biological Parameters in an Epidemiology Problem
author Benedito, Antone dos Santos [UNESP]
author_facet Benedito, Antone dos Santos [UNESP]
Pio dos Santos, Fernando Luiz [UNESP]
Rojas, I
Joya, G.
Catala, A.
author_role author
author2 Pio dos Santos, Fernando Luiz [UNESP]
Rojas, I
Joya, G.
Catala, A.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Benedito, Antone dos Santos [UNESP]
Pio dos Santos, Fernando Luiz [UNESP]
Rojas, I
Joya, G.
Catala, A.
dc.subject.por.fl_str_mv Computational population dynamics
Ordinary differential system
Aedes
Dengue
topic Computational population dynamics
Ordinary differential system
Aedes
Dengue
description In this paper, we describe a study of a parameter estimation technique to estimate a set of unknown biological parameters of a nonlinear dynamic model of dengue. We also explore a Levenberg-Marquardt (LM) algorithm to minimize the cost function. A classical mathematical model describes the dynamics of mosquitoes in water and winged phases, where the data are available. The main interest is to fit the model to the data taking into account the parameters estimated. Numerical simulations were performed and results showed the robustness of LM in estimating the important parameters in the dengue disease problem.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01
2018-11-26T17:55:11Z
2018-11-26T17:55:11Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/978-3-319-59153-7_10
Advances In Computational Intelligence, Iwann 2017, Pt I. Cham: Springer International Publishing Ag, v. 10305, p. 112-122, 2017.
0302-9743
http://hdl.handle.net/11449/164584
10.1007/978-3-319-59153-7_10
WOS:000443108200010
WOS000443108200010.pdf
url http://dx.doi.org/10.1007/978-3-319-59153-7_10
http://hdl.handle.net/11449/164584
identifier_str_mv Advances In Computational Intelligence, Iwann 2017, Pt I. Cham: Springer International Publishing Ag, v. 10305, p. 112-122, 2017.
0302-9743
10.1007/978-3-319-59153-7_10
WOS:000443108200010
WOS000443108200010.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Advances In Computational Intelligence, Iwann 2017, Pt I
0,295
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 112-122
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808128244090667008

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