Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
KOZEL, T. STARÝ, M.
Originální název
Adaptive stochastic management of the storage function for a large open reservoir using an artificial intelligence method
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
The design and evaluation of algorithms for adaptive stochastic control of reservoir function of the water reservoir using artificial intelligence methods (learning fuzzy model and neural networks) are described in this article. This procedure was tested on an artificial reservoir. Reservoir parameters have been designed to cause critical disturbances during the control process, and therefore the influences of control algorithms can be demonstrated in the course of controlled outflow of water from the reservoir. The results of the stochastic adaptive models were compared. Further, stochastic model results were compared with a resultant course of management obtained using the method of classical optimisation (differential evolution), which used stochastic forecast data from real series (100% forecast). Finally, the results of the dispatcher graph and adaptive stochastic control were compared. Achieved results of adaptive stochastic management provide inspiration for continuing research in the field.
Klíčová slova
Stochastic; Artificial intelligence; Storage function; Optimisation
Autoři
KOZEL, T.; STARÝ, M.
Vydáno
15. 12. 2019
Nakladatel
Journal of Hydrology and Hydromechanics
Místo
Bratislava
ISSN
0042-790X
Periodikum
Ročník
64
Číslo
4
Stát
Slovenská republika
Strany od
314
Strany do
321
Strany počet
8
URL
http://www.uh.sav.sk/Portals/16/vc_articles/2019_67_4_Kozel_314.pdf
Plný text v Digitální knihovně
http://hdl.handle.net/11012/200894
BibTex
@article{BUT161073, author="Tomáš {Kozel} and Miloš {Starý}", title="Adaptive stochastic management of the storage function for a large open reservoir using an artificial intelligence method", journal="Journal of Hydrology and Hydromechanics", year="2019", volume="64", number="4", pages="314--321", doi="10.2478/johh-2019-0021", issn="0042-790X", url="http://www.uh.sav.sk/Portals/16/vc_articles/2019_67_4_Kozel_314.pdf" }