Séminaires DO

Organisation : Carine Jauberthie - Lieu habituel : salle EUROPE du LAAS

Le département DO fédère les activités de recherche de trois équipes de recherche du LAAS: Diagnostic Supervision et Conduite, Méthodes et Algorithmes en Commande, Recherche Opérationnelle/Optimisation Combinatoire/Contraintes.

A venir / Archives

Mardi 5 Février 2019 - Salle Bardeen - 14h30 - Nathalie Verdière

Identifiability analysis and parameter estimation in PDE models.

2019 - Kenneth Sörensen ; Daniele Vigo ;

Résumé des prochains séminaires

Identifiability analysis and parameter estimation in PDE models.

We investigate identifiability and estimation of parameters in partial differential equations (PDE) models. An elimination method used in the case of ordinary differential equations (EDOs) is extended to PDE models. This elimination method produces specific relations depending on the inputs, outputs and the parameters of the model. It can be done either by hand or by a dedicated software. Contrary to the use of a dedicated software, elimination done by hand permits to control all the steps of the elimination procedure with respect to the regularity of the solutions of the model. However, from non well-defined relations, it is sometimes possible with some theoretical considerations to produce new relations usable for an identifiability study and an elimination procedure.  This work will be applied to a chikungunya epidemic transmission model which  incorporates the spatial mobility of humans. Indeed, it is a factor that has influenced the re-emergence of several epidemic diseases. The displacement of mosquitoes is omitted since it is limited to a few meters. This model couples a mosquito dynamics model and a transmission virus model between humans and mosquitoes populations. The mosquito larvae and the human population are supposed to be observed. The complete model is then composed of a reaction-diffusion system coupled with ordinary differential equations. Based on the previous theoretical results, identifiability and estimation of this parametric model will be carried out.

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