Publication detail

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

KOZEL, T. STARÝ, M.

Original Title

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

Type

journal article in Web of Science

Language

English

Original Abstract

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

Keywords

Stochastic; Artificial intelligence; Storage function; Optimisation.

Authors

KOZEL, T.; STARÝ, M.

Released

1. 6. 2022

Publisher

Sciendo

ISBN

0042-790X

Periodical

Journal of Hydrology and Hydromechanics

Year of study

70

Number

2

State

Slovak Republic

Pages from

213

Pages to

221

Pages count

9

URL

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

Full text in the Digital Library

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"
}