• DocumentCode
    189367
  • Title

    Dynamical model identification of population of oysters for water quality monitoring

  • Author

    Ahmed, Hameeza ; Ushirobira, Rosane ; Efimov, D. ; Tran, Duke ; Massabuau, Jean-Charles

  • Author_Institution
    Non-A team at Inria, Lille, France
  • fYear
    2014
  • fDate
    24-27 June 2014
  • Firstpage
    152
  • Lastpage
    157
  • Abstract
    The 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 model takes into account the influence of environmental conditions using measurements of the sunlight intensity, the moonlight and tide levels. A possible influence of the internal circadian/circatidal clocks is also analyzed. Through this application, it is demonstrated that the developed dynamical model can be used for estimation of the normal physiological rhythms of permanently immersed oysters and considered for detection of perturbations of these rhythms due to changes in the water quality, i.e. for ecological monitoring.
  • Keywords
    autoregressive processes; ecology; environmental monitoring (geophysics); identification; physiological models; sunlight; tides; water pollution control; water quality; Bay of Arcachon; France; NARX model; bivalves; dynamical model identification; ecological monitoring; internal circadian/circatidal clocks; moonlight; natural environmental conditions; nonlinear autoregressive exogenous model; normal physiological rhythms estimation; oysters population; perturbations detection; physiological model identification; sunlight intensity; tide levels; valve activity measurements; water quality monitoring; Animals; Biological system modeling; Monitoring; Sea measurements; Sociology; Statistics; Valves;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2014 European
  • Conference_Location
    Strasbourg
  • Print_ISBN
    978-3-9524269-1-3
  • Type

    conf

  • DOI
    10.1109/ECC.2014.6862479
  • Filename
    6862479