Detail publikačního výsledku

Adaptive stochastic management of the storage function for a large, open reservoir using learned fuzzy models

KOZEL, T.; STARÝ, M.

Originální název

Adaptive stochastic management of the storage function for a large, open reservoir using learned fuzzy models

Anglický název

Adaptive stochastic management of the storage function for a large, open reservoir using learned fuzzy models

Druh

Článek WoS

Originální abstrakt

The design and evaluation of algorithms for adaptive stochastic control of the reservoir function of a water reservoir using an artificial intelligence method (learned fuzzy model) are described in this article. This procedure was tested on the Vranov reservoir (Czech Republic). Stochastic model results were compared with the results of deterministic management obtained using the method of classical optimisation (differential evolution). The models used for controlling of reservoir outflow used single quantile from flow duration curve values or combinations of quantile values from flow duration curve for determination of controlled outflow. Both methods were also tested on forecast data from real series (100% forecast). Finally, the results of the dispatcher graph, adaptive deterministic control and adaptive stochastic control were compared. Achieved results of adaptive stochastic management were better than results provided by dispatcher graph and provide inspiration for continuing research in the field

Anglický abstrakt

The design and evaluation of algorithms for adaptive stochastic control of the reservoir function of a water reservoir using an artificial intelligence method (learned fuzzy model) are described in this article. This procedure was tested on the Vranov reservoir (Czech Republic). Stochastic model results were compared with the results of deterministic management obtained using the method of classical optimisation (differential evolution). The models used for controlling of reservoir outflow used single quantile from flow duration curve values or combinations of quantile values from flow duration curve for determination of controlled outflow. Both methods were also tested on forecast data from real series (100% forecast). Finally, the results of the dispatcher graph, adaptive deterministic control and adaptive stochastic control were compared. Achieved results of adaptive stochastic management were better than results provided by dispatcher graph and provide inspiration for continuing research in the field

Klíčová slova

Stochastic; Artificial intelligence; Storage function; Optimisation.

Klíčová slova v angličtině

Stochastic; Artificial intelligence; Storage function; Optimisation.

Autoři

KOZEL, T.; STARÝ, M.

Rok RIV

2023

Vydáno

01.06.2022

Nakladatel

Sciendo

ISSN

0042-790X

Periodikum

Journal of Hydrology and Hydromechanics

Svazek

70

Číslo

2

Stát

Slovenská republika

Strany od

213

Strany do

221

Strany počet

9

URL

https://www.sciendo.com/article/10.2478/johh-2022-0010

Plný text v Digitální knihovně

http://hdl.handle.net/11012/208230

BibTex

@article{BUT178574,
  author="Tomáš {Kozel} and Miloš {Starý}",
  title="Adaptive stochastic management of the storage function for a large, open reservoir using learned fuzzy models",
  journal="Journal of Hydrology and Hydromechanics",
  year="2022",
  volume="70",
  number="2",
  pages="213--221",
  doi="10.2478/johh-2022-0010",
  issn="0042-790X",
  url="https://www.sciendo.com/article/10.2478/johh-2022-0010"
}

Dokumenty

10.2478_johh-2022-0010