An adaptive algorithm of hybrid optimization method for strategic control of water reservoir with using support vector machines

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F16%3APU119583" target="_blank" >RIV/00216305:26110/16:PU119583 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5593/SGEM2016/B31/S12.008" target="_blank" >http://dx.doi.org/10.5593/SGEM2016/B31/S12.008</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5593/SGEM2016/B31/S12.008" target="_blank" >10.5593/SGEM2016/B31/S12.008</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An adaptive algorithm of hybrid optimization method for strategic control of water reservoir with using support vector machines

Popis výsledku v původním jazyce

The aim of strategic control is the effort to achieve optimal water outflow from reservoir. Classic strategic control of water reservoirs are based mainly on the rules and rules curves, which are created by generalization of historical data of water inflows to the reservoirs and water outflow. Discharge series are changing in the time due to expected climate change. It is necessary to looking for intelligent water outflow control, which will allow to react on these hydrological changes and contribute to the efficient use of accumulated water for ensure water demand. The paper will describe the algorithm based on adaptive control. The normal adaptive control required knowledge of the water flow medium-term prediction into the reservoir. The created algorithm of intelligent control does not require knowledge of hydrological predictions. This control method is based on a suitable combination optimization method with the Support vector machines method. The control algorithm is one of the possible measures to mitigate the negative impacts of droughts and water scarcity. The algorithm of hybrid optimization method for strategic control of water reservoir will be detail describe in this paper.

Název v anglickém jazyce

An adaptive algorithm of hybrid optimization method for strategic control of water reservoir with using support vector machines

Popis výsledku anglicky

The aim of strategic control is the effort to achieve optimal water outflow from reservoir. Classic strategic control of water reservoirs are based mainly on the rules and rules curves, which are created by generalization of historical data of water inflows to the reservoirs and water outflow. Discharge series are changing in the time due to expected climate change. It is necessary to looking for intelligent water outflow control, which will allow to react on these hydrological changes and contribute to the efficient use of accumulated water for ensure water demand. The paper will describe the algorithm based on adaptive control. The normal adaptive control required knowledge of the water flow medium-term prediction into the reservoir. The created algorithm of intelligent control does not require knowledge of hydrological predictions. This control method is based on a suitable combination optimization method with the Support vector machines method. The control algorithm is one of the possible measures to mitigate the negative impacts of droughts and water scarcity. The algorithm of hybrid optimization method for strategic control of water reservoir will be detail describe in this paper.

Druh

D - Stať ve sborníku

CEP obor

DA - Hydrologie a limnologie

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

SGEM Conference Proceedings

ISBN

978-619-7105-61-2

ISSN

1314-2704

e-ISSN

—

Počet stran výsledku

7

Strana od-do

55-61

Název nakladatele

STEF92 Technology Ltd.

Místo vydání

51 Alexander Malinov Blvd., 1712, Sofia, Bulgari

Místo konání akce

Albena

Datum konání akce

30. 6. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000391653400008