Adaptive stochastic management of the storage function for a large open reservoir using an artificial intelligence method
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F19%3APU134679" target="_blank" >RIV/00216305:26110/19:PU134679 - isvavai.cz</a>
Result on the web
<a href="http://www.uh.sav.sk/Portals/16/vc_articles/2019_67_4_Kozel_314.pdf" target="_blank" >http://www.uh.sav.sk/Portals/16/vc_articles/2019_67_4_Kozel_314.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2478/johh-2019-0021" target="_blank" >10.2478/johh-2019-0021</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive stochastic management of the storage function for a large open reservoir using an artificial intelligence method
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10501 - Hydrology
Result continuities
Project
—
Continuities
O - Projekt operacniho programu
Others
Publication year
2019
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
64
Issue of the periodical within the volume
4
Country of publishing house
SK - SLOVAKIA
Number of pages
8
Pages from-to
314-321
UT code for WoS article
000497193600003
EID of the result in the Scopus database
2-s2.0-85076305067