Adaptive stochastic management of the storage function for a large, open reservoir using learned fuzzy models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F22%3APU145097" target="_blank" >RIV/00216305:26110/22:PU145097 - isvavai.cz</a>
Result on the web
<a href="https://www.sciendo.com/article/10.2478/johh-2022-0010" target="_blank" >https://www.sciendo.com/article/10.2478/johh-2022-0010</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2478/johh-2022-0010" target="_blank" >10.2478/johh-2022-0010</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive stochastic management of the storage function for a large, open reservoir using learned fuzzy models
Original language description
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
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10501 - Hydrology
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Hydrology and Hydromechanics
ISSN
0042-790X
e-ISSN
1338-4333
Volume of the periodical
70
Issue of the periodical within the volume
2
Country of publishing house
SK - SLOVAKIA
Number of pages
9
Pages from-to
213-221
UT code for WoS article
000797305300006
EID of the result in the Scopus database
2-s2.0-85131138728