Calibrating a large network model describing the transmission dynamics of the human papillomavirus (HPV) using a Particle Swarm Optimization (PSO) algorithm in a distributed computing environment

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dc.contributor.affiliationFacultad de Administración y Dirección de Empresas
dc.contributor.affiliationDepartamento de Matemática Aplicada
dc.contributor.affiliationEscuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica
dc.contributor.affiliationInstituto Universitario de Matemática Multidisciplinar
dc.contributor.authorAcedo Rodríguez, Luises_ES
dc.contributor.authorBurgos-Simon, Clara
dc.contributor.authorHidalgo, José-Ignacioes_ES
dc.contributor.authorSánchez-Alonso, Víctores_ES
dc.contributor.authorVillanueva Micó, Rafael Jacinto
dc.contributor.authorVillanueva-Oller, Javieres_ES
dc.contributor.funderMinisterio de Economía y Competitividades_ES
dc.contributor.funderMinisterio de Economía, Industria y Competitividades_ES
dc.date.accessioned2020-04-17T12:48:00Z
dc.date.available2020-04-17T12:48:00Z
dc.date.issued2018es_ES
dc.description.abstract[EN] Working in large networks applied to epidemiological-type models has led us to design a simple but e↵ective computed distributed environment to perform a large amount of model simulations in a reasonable time in order to study the behavior of these models and to calibrate them. Finding the model parameters that best fit the available data in the designed distributed computing environment becomes a challenge and it is necessary to implement reliable algorithms for model calibration. In this paper, we have adapted the random PSO algorithm to our distributed computing environment to be applied to the calibration of a Papillomavirus transmission dynamics model on a lifetime sexual partners network. And we have obtained a good fitting saving time and calculations compared with the exhaustive searching strategy we have been using so far.en_EN
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationAcedo Rodríguez, L.; Burgos-Simon, C.; Hidalgo, J.; Sánchez-Alonso, V.; Villanueva Micó, RJ.; Villanueva-Oller, J. (2018). Calibrating a large network model describing the transmission dynamics of the human papillomavirus (HPV) using a Particle Swarm Optimization (PSO) algorithm in a distributed computing environment. International Journal of High Performance Computing Applications. 32(5):721-728. https://doi.org/10.1177/1094342017697862es_ES
dc.description.issue5es_ES
dc.description.referencesAcedo, L., Lamprianidou, E., Moraño, J.-A., Villanueva-Oller, J., & Villanueva, R.-J. (2015). Firing patterns in a random network cellular automata model of the brain. Physica A: Statistical Mechanics and its Applications, 435, 111-119. doi:10.1016/j.physa.2015.05.017es_ES
dc.description.referencesAcedo, L., Moraño, J.-A., Villanueva, R.-J., Villanueva-Oller, J., & Díez-Domingo, J. (2011). Using random networks to study the dynamics of respiratory syncytial virus (RSV) in the Spanish region of Valencia. Mathematical and Computer Modelling, 54(7-8), 1650-1654. doi:10.1016/j.mcm.2010.11.068es_ES
dc.description.referencesCastellsagué, X., Iftner, T., Roura, E., Vidart, J. A., Kjaer, S. K., … Bosch, F. X. (2012). Prevalence and genotype distribution of human papillomavirus infection of the cervix in Spain: The CLEOPATRE study. Journal of Medical Virology, 84(6), 947-956. doi:10.1002/jmv.23282es_ES
dc.description.referencesCortés, J.-C., Colmenar, J.-M., Hidalgo, J.-I., Sánchez-Sánchez, A., Santonja, F.-J., & Villanueva, R.-J. (2016). Modeling and predicting the Spanish Bachillerato academic results over the next few years using a random network model. Physica A: Statistical Mechanics and its Applications, 442, 36-49. doi:10.1016/j.physa.2015.08.032es_ES
dc.description.referencesElbasha, E. H., Dasbach, E. J., & Insinga, R. P. (2007). Model for Assessing Human Papillomavirus Vaccination Strategies. Emerging Infectious Diseases, 13(1), 28-41. doi:10.3201/eid1301.060438es_ES
dc.description.referencesGonzález-Parra, G., Villanueva, R.-J., Ruiz-Baragaño, J., & Moraño, J.-A. (2015). Modelling influenza A(H1N1) 2009 epidemics using a random network in a distributed computing environment. Acta Tropica, 143, 29-35. doi:10.1016/j.actatropica.2014.12.008es_ES
dc.description.referencesKhemka, N., & Jacob, C. (2010). Exploratory Toolkit for Evolutionary and Swarm-Based Optimization. The Mathematica Journal, 11(3), 376-391. doi:10.3888/tmj.11.3-5es_ES
dc.description.sponsorshipThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been partially supported by the Ministerio de Economa y Competitividad Grants MTM2013-41765-P and TIN 2014-54806-R.es_ES
dc.description.upvformatpfin728es_ES
dc.description.upvformatpinicio721es_ES
dc.description.volume32es_ES
dc.identifier.doi10.1177/1094342017697862es_ES
dc.identifier.issn1094-3420es_ES
dc.identifier.urihttps://riunet.upv.es/handle/10251/140834
dc.languageIngléses_ES
dc.publisherSAGE Publicationses_ES
dc.relation.ispartofInternational Journal of High Performance Computing Applicationses_ES
dc.relation.pasarelaS\337118es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TIN2014-54806-R/ES/DESARROLLO DE SISTEMAS ADAPTATIVOS Y BIOINSPIRADOS PARA EL CONTROL GLUCEMICO CON INFUSORES SUBCUTANEOS CONTINUOS DE INSULINA Y MONITORES CONTINUOS DE GLUCOSA/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//MTM2013-41765-P/ES/METODOS COMPUTACIONALES PARA ECUACIONES DIFERENCIALES ALEATORIAS: TEORIA Y APLICACIONES/es_ES
dc.relation.publisherversionhttps://doi.org/10.1177/1094342017697862es_ES
dc.relation.references10.1016/j.physa.2015.05.017es_ES
dc.relation.references10.1016/j.mcm.2010.11.068es_ES
dc.relation.references10.1002/jmv.23282es_ES
dc.relation.references10.1016/j.physa.2015.08.032es_ES
dc.relation.references10.3201/eid1301.060438es_ES
dc.relation.references10.1016/j.actatropica.2014.12.008es_ES
dc.relation.references10.3888/tmj.11.3-5es_ES
dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectNetwork modelses_ES
dc.subjectDistributed computing paradigmes_ES
dc.subjectModel calibrationes_ES
dc.subjectParticle swarm optimizationes_ES
dc.subjectHuman papillomaviruses_ES
dc.subject.classificationMATEMATICA APLICADAes_ES
dc.titleCalibrating a large network model describing the transmission dynamics of the human papillomavirus (HPV) using a Particle Swarm Optimization (PSO) algorithm in a distributed computing environmentes_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier557012
person.identifier823
person.identifier.orcid0000-0001-6385-4263
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