• DocumentCode
    707009
  • Title

    Identifying lake longer-term dynamics via fuzzy relations and non-linear Kalman filters

  • Author

    Kolemishevska-Gugulovska, Tatjana D. ; Dimirovski, Georgi M. ; Dinibutun, A. Talha ; Gough, Norman E.

  • Author_Institution
    ASE Inst., Sts. Cyril & Methodius Univ., Skopje, Macedonia
  • fYear
    1999
  • fDate
    Aug. 31 1999-Sept. 3 1999
  • Firstpage
    3982
  • Lastpage
    3988
  • Abstract
    A novel simulation modelling technique that may be used to reconstruct or predict longer-term water level dynamics of lakes and reservoirs has been elaborated. On the grounds of the conservation law and a kind of self-regulation property of these lakes, by using Kalman filters for the unmeasurable part of hydrologic-cycle dynamical path and output observation equation in traditional and in fuzzy-relational a simulation modelling technique was developed that is believed to have wide applicability. It has been applied to reconstruct successfully the behaviour of Ohridean and Prespanean Lakes during various time periods, despite the available records are interrupted, uncertain and unreliable due to historical circumstances.
  • Keywords
    Kalman filters; ecology; fuzzy set theory; lakes; nonlinear filters; Ohridean Lake; Prespanean Lake; fuzzy relations; lake longer-term dynamics identification; lakes longer-term water level dynamics prediction; nonlinear Kalman filters; reservoirs longer-term water level dynamics prediction; simulation modelling technique; Biological system modeling; Computational modeling; Data models; Lakes; Mathematical model; Water resources; Aquatic ecosystems; hydrologic cycle; identification; simulation; water level dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 1999 European
  • Conference_Location
    Karlsruhe
  • Print_ISBN
    978-3-9524173-5-5
  • Type

    conf

  • Filename
    7099954