A stochastic approach to the operative control of flood flows through a reservoir

The contribution focuses on the design of a control algorithm aimed at the operative control of runoff water from a reservoir during flood situations. Management is based on the stochastically specified forecast of water inflow into the reservoir. From a mathematical perspective, the solved task pre...

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Main Authors: Jaroš Lubomír, Starý Miloš, Březková Lucie
Format: Article
Language:English
Published: Sciendo 2016-03-01
Series:Journal of Hydrology and Hydromechanics
Subjects:
Online Access:https://doi.org/10.1515/johh-2016-0012
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author Jaroš Lubomír
Starý Miloš
Březková Lucie
author_facet Jaroš Lubomír
Starý Miloš
Březková Lucie
author_sort Jaroš Lubomír
collection DOAJ
description The contribution focuses on the design of a control algorithm aimed at the operative control of runoff water from a reservoir during flood situations. Management is based on the stochastically specified forecast of water inflow into the reservoir. From a mathematical perspective, the solved task presents the control of a dynamic system whose predicted hydrological input (water inflow) is characterised by significant uncertainty. The algorithm uses a combination of simulation model data, in which the position of the bottom outlets is sought via nonlinear optimisation methods, and artificial intelligence methods (adaptation and fuzzy model). The task is written in the technical computing language MATLAB using the Fuzzy Logic Toolbox.
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spelling doaj.art-aa912b1438254cb6a20daa92c4b1de182022-12-21T21:14:50ZengSciendoJournal of Hydrology and Hydromechanics0042-790X2016-03-01641919610.1515/johh-2016-0012johh-2016-0012A stochastic approach to the operative control of flood flows through a reservoirJaroš Lubomír0Starý Miloš1Březková Lucie2 Povodí Odry, State Enterprise, Varenská 3101/49, 701 26 Ostrava, Czech Republic. Brno Technical University, Faculty of Civil Engineering, Institute of Landscape Water Management, Žižkova 17, 602 00, Brno, Czech Republic. Brno Technical University, Faculty of Civil Engineering, Institute of Landscape Water Management, Žižkova 17, 602 00, Brno, Czech Republic.The contribution focuses on the design of a control algorithm aimed at the operative control of runoff water from a reservoir during flood situations. Management is based on the stochastically specified forecast of water inflow into the reservoir. From a mathematical perspective, the solved task presents the control of a dynamic system whose predicted hydrological input (water inflow) is characterised by significant uncertainty. The algorithm uses a combination of simulation model data, in which the position of the bottom outlets is sought via nonlinear optimisation methods, and artificial intelligence methods (adaptation and fuzzy model). The task is written in the technical computing language MATLAB using the Fuzzy Logic Toolbox.https://doi.org/10.1515/johh-2016-0012operative control of reservoirartificial intelligencefuzzy inference systemneural networksstochastic forecaststochastic control of reservoirprinciple of adaptation
spellingShingle Jaroš Lubomír
Starý Miloš
Březková Lucie
A stochastic approach to the operative control of flood flows through a reservoir
Journal of Hydrology and Hydromechanics
operative control of reservoir
artificial intelligence
fuzzy inference system
neural networks
stochastic forecast
stochastic control of reservoir
principle of adaptation
title A stochastic approach to the operative control of flood flows through a reservoir
title_full A stochastic approach to the operative control of flood flows through a reservoir
title_fullStr A stochastic approach to the operative control of flood flows through a reservoir
title_full_unstemmed A stochastic approach to the operative control of flood flows through a reservoir
title_short A stochastic approach to the operative control of flood flows through a reservoir
title_sort stochastic approach to the operative control of flood flows through a reservoir
topic operative control of reservoir
artificial intelligence
fuzzy inference system
neural networks
stochastic forecast
stochastic control of reservoir
principle of adaptation
url https://doi.org/10.1515/johh-2016-0012
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