dc.contributor.author |
Villanueva Micó, Rafael Jacinto
|
es_ES |
dc.contributor.author |
Hidalgo, J.I.
|
es_ES |
dc.contributor.author |
Cervigon, Carlos
|
es_ES |
dc.contributor.author |
Villanueva-Oller, Javier
|
es_ES |
dc.contributor.author |
Cortés, J.-C.
|
es_ES |
dc.date.accessioned |
2020-04-17T12:51:54Z |
|
dc.date.available |
2020-04-17T12:51:54Z |
|
dc.date.issued |
2019 |
es_ES |
dc.identifier.issn |
1568-4946 |
es_ES |
dc.identifier.uri |
http://hdl.handle.net/10251/140966 |
|
dc.description.abstract |
[EN] Recently, the transmission dynamics of the Human Papillomavirus (HPV) has been studied. In previous works, we have designed and implemented a computational model (agent-based simulation model) where the contagion of the HPV is described on a network of lifetime sexual partners. The run of a single simulation of this computational model, composed of a network with 500 000 nodes, takes about one hour and a half. In addition to set an adequate model, finding out the model parameters that best fit the proposed model to the available data of prevalence is a crucial goal. Taking into account that the necessary number of simulations to perform the calibration of the model may be very high, the aforementioned goal may become unaffordable. In this paper, we present a procedure to fit the proposed HPV model to the available data and the design of an asynchronous version of the Particle Swarm Optimization (PSO) algorithm adapted to the distributed computing environment. In the process, the number of particles used in PSO should be set carefully looking for a compromise between quality of the solutions and computation time. Another feature of the procedure presented here is that we want to capture the intrinsic uncertainty in the data (data come from a survey) when calibrating the model. To do so, we also propose the design of an algorithm to select the model parameter sets obtained during the calibration that best capture the data uncertainty. |
es_ES |
dc.description.sponsorship |
This work has been supported by the Spanish Ministerio de Economia y Competitividad grants MTM2017-89664-P, TIN2014-54806-R and RTI2018-095180-B-I00, Grants Y2018/NMT-4668 (Micro-Stres-MAP-CM) and GenObIA-CM (S2017/BMD-3773) financed by the Community of Madrid, Spain and co-financed with EU Structural Funds, Spain, and by GLENO project financed by Fundacion Eugenio Rodriguez Pascual, Spain. |
es_ES |
dc.language |
Inglés |
es_ES |
dc.publisher |
Elsevier |
es_ES |
dc.relation.ispartof |
Applied Soft Computing |
es_ES |
dc.rights |
Reserva de todos los derechos |
es_ES |
dc.subject |
HPV transmission dynamics |
es_ES |
dc.subject |
Computational random network model |
es_ES |
dc.subject |
Model calibration |
es_ES |
dc.subject |
Particle swarm optimization |
es_ES |
dc.subject |
Uncertainty quantification |
es_ES |
dc.subject |
Agent-based simulation modeling |
es_ES |
dc.subject.classification |
MATEMATICA APLICADA |
es_ES |
dc.title |
Calibration of an agent-based simulation model to the data of women infected by Human Papillomavirus with uncertainty |
es_ES |
dc.type |
Artículo |
es_ES |
dc.identifier.doi |
10.1016/j.asoc.2019.04.015 |
es_ES |
dc.relation.projectID |
info: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.projectID |
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095180-B-I00/ES/SISTEMA ADAPTATIVO BIOINSPIRADO PARA EL CONTROL GLUCEMICO BASADO EN SENSORES Y ACCESORIOS INTELIGENTES/ |
es_ES |
dc.relation.projectID |
info:eu-repo/grantAgreement/CAM//Y2018%2FNMT- 4668/ |
es_ES |
dc.relation.projectID |
info:eu-repo/grantAgreement/CAM//S2017%2FBMD-3773/ |
es_ES |
dc.relation.projectID |
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-89664-P/ES/PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES/ |
es_ES |
dc.rights.accessRights |
Abierto |
es_ES |
dc.contributor.affiliation |
Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada |
es_ES |
dc.description.bibliographicCitation |
Villanueva Micó, RJ.; Hidalgo, J.; Cervigon, C.; Villanueva-Oller, J.; Cortés, J. (2019). Calibration of an agent-based simulation model to the data of women infected by Human Papillomavirus with uncertainty. Applied Soft Computing. 80:546-556. https://doi.org/10.1016/j.asoc.2019.04.015 |
es_ES |
dc.description.accrualMethod |
S |
es_ES |
dc.relation.publisherversion |
https://doi.org/10.1016/j.asoc.2019.04.015 |
es_ES |
dc.description.upvformatpinicio |
546 |
es_ES |
dc.description.upvformatpfin |
556 |
es_ES |
dc.type.version |
info:eu-repo/semantics/publishedVersion |
es_ES |
dc.description.volume |
80 |
es_ES |
dc.relation.pasarela |
S\384418 |
es_ES |
dc.contributor.funder |
Comunidad de Madrid |
es_ES |
dc.contributor.funder |
European Commission |
es_ES |
dc.contributor.funder |
Agencia Estatal de Investigación |
es_ES |
dc.contributor.funder |
Fundación Eugenio Rodriguez Pascual |
es_ES |
dc.contributor.funder |
Ministerio de Economía y Competitividad |
es_ES |