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dc.rights.licenseopenen_US
hal.structure.identifierNon-Asymptotic estimation for online systems [NON-A]
dc.contributor.authorAHMED, Hafiz
hal.structure.identifierNon-Asymptotic estimation for online systems [NON-A]
dc.contributor.authorUSHIROBIRA, Rosane
hal.structure.identifierNon-Asymptotic estimation for online systems [NON-A]
dc.contributor.authorEFIMOV, Denis
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorTRAN, Damien
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorSOW, Mohamedou
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorCIRET, Pierre
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorMASSABUAU, Jean-Charles
dc.date.accessioned2024-03-28T14:28:56Z
dc.date.available2024-03-28T14:28:56Z
dc.date.issued2017-06
dc.identifier.issn0018-9472en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/189073
dc.description.abstractEnThe measurements of valve activity in a population of bivalves under natural environmental conditions (16 oysters in the Bay of Arcachon, France) are used for a physiological model identification. A nonlinear auto-regressive exogenous (NARX) model is designed and tested. The method to design the model has two parts. 1) Structure of the model: The model takes into account the influence of environmental conditions using measurements of the sunlight intensity, the moonlight, tide levels, precipitation and water salinity levels. A possible influence of the internal circadian/circatidal clocks is also analyzed. 2) Least square calculation of the model parameters. Through this study, it is demonstrated that the developed dynamical model of the oyster valve movement can be used for estimating normal physiological rhythms of permanently immersed oysters and can be considered for detecting perturbations of these rhythms due to changes in the water quality, i.e. for ecological monitoring.
dc.language.isoENen_US
dc.subject.enSystem Identification
dc.subject.enEcological Monitoring
dc.subject.enOyster Population
dc.subject.enDynamic Model
dc.subject.enCircadian Rhythm Modeling
dc.subject.enBioindicator
dc.title.enMonitoring biological rhythms through the dynamic model identification of an oyster population
dc.typeArticle de revueen_US
dc.identifier.doi10.1109/TSMC.2016.2523923en_US
dc.subject.halSciences de l'ingénieur [physics]/Automatique / Robotiqueen_US
dc.subject.halSciences du Vivant [q-bio]/Ecologie, Environnement/Ecosystèmesen_US
dc.subject.halMathématiques [math]/Théorie des représentations [math.RT]en_US
bordeaux.journalIEEE transactions on systems, man, and cyberneticsen_US
bordeaux.volume47en_US
bordeaux.hal.laboratoriesEPOC : Environnements et Paléoenvironnements Océaniques et Continentaux - UMR 5805en_US
bordeaux.issue6en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcehal
hal.identifierhal-01220311
hal.version1
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
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