STOCHASTIC MANAGEMENT OF THE OPEN LARGE WATER RESERVOIR WITH STORAGE FUNCTION WITH USING FUZZY LOGIC

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F16%3APU119728" target="_blank" >RIV/00216305:26110/16:PU119728 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.5593/SGEM2016/B31/S12.110" target="_blank" >http://dx.doi.org/10.5593/SGEM2016/B31/S12.110</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5593/SGEM2016/B31/S12.110" target="_blank" >10.5593/SGEM2016/B31/S12.110</a>

Result language

angličtina

Original language name

STOCHASTIC MANAGEMENT OF THE OPEN LARGE WATER RESERVOIR WITH STORAGE FUNCTION WITH USING FUZZY LOGIC

Original language description

Described models are used random forecasting period of flow line with different length. The length is shorter than 1 year. Forecasting period of flow line is transformed to line of managing discharges with same length as forecast. Adaptive managing is used only first value of line of discharges. Stochastic management is worked with dispersion of controlling discharge value. Main advantage stochastic management is fun of possibilities. In article is described construction and evaluation of adaptive stochastic model base on fuzzy logic. Models were used for stochastic management of open large water reservoir with storage function. The fuzzy model is used fuzzy logic as replacement of classic optimization algorithm. If model is given pattern matrix of management, matrix is given by model base on classic optimization algorithm, and forecast, controlling discharge value is computed by model for chosen probability of controlling discharge value. Model was tested and validated on made up large open water reservoir. Results were evaluated and were compared with model base on traditional algorithms. Evaluation was done for 100% forecast (forecasted values are real values) and for chosen probability of discharge. The management of the large open water reservoir with storage function was logically. The main advantage of fuzzy model is computing speed. Classical optimization model was needed much more time for same calculation as fuzzy model, therefore classic model was used parallel computing.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2016

Confidentiality

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

Article name in the collection

SGEM Conference Proceedingsc

ISBN

978-619-7105-61-2

ISSN

1314-2704

e-ISSN

—

Number of pages

6

Pages from-to

55-61

Publisher name

STEF92 Technology Ltd.

Place of publication

51 Alexander Malinov Blvd., 1712, Sofia, Bulgari

Event location

Albena

Event date

Jun 30, 2016

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000391653400087