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
Link To Document