Detail publikačního výsledku

Adaptive stochastic management of the storage function for a large open reservoir using an artificial intelligence method

KOZEL, T.; STARÝ, M.

Originální název

Adaptive stochastic management of the storage function for a large open reservoir using an artificial intelligence method

Anglický název

Adaptive stochastic management of the storage function for a large open reservoir using an artificial intelligence method

Druh

Článek WoS

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.

Anglický 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

Klíčová slova v angličtině

Stochastic; Artificial intelligence; Storage function; Optimisation

Autoři

KOZEL, T.; STARÝ, M.

Rok RIV

2020

Vydáno

15.12.2019

Nakladatel

Journal of Hydrology and Hydromechanics

Místo

Bratislava

ISSN

0042-790X

Periodikum

Journal of Hydrology and Hydromechanics

Svazek

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"
}

Dokumenty

10.2478_johh-2019-0021