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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10501 - Hydrology

Projekt

—

Návaznosti

O - Projekt operacniho programu

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Hydrology and Hydromechanics

ISSN

0042-790X

e-ISSN

1338-4333

Svazek periodika

64

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

8

Strana od-do

314-321

Kód UT WoS článku

000497193600003

EID výsledku v databázi Scopus

2-s2.0-85076305067