Detail publikace

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

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

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

Klíčová slova

Stochastic; Artificial intelligence; Storage function; Optimisation.

Autoři

KOZEL, T.; STARÝ, M.

Vydáno

1. 6. 2022

Nakladatel

Sciendo

ISSN

0042-790X

Periodikum

Journal of Hydrology and Hydromechanics

Ročník

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"
}