In: Journal of Hydrology and Hydromechanics, vol. 67, no. 4
Tomas Kozel - Milos Stary
Details:
Year, pages: 2019, 314 - 321
Language: eng
Keywords:
Stochastic; Artificial intelligence; Storage function; Optimisation.
Original source URL: http://www.ih.sav.sk/jhh
About article:
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.
How to cite:
ISO 690:
Kozel, T., Stary, M. 2019. Adaptive stochastic management of the storage function for a large open
reservoir using an artificial intelligence method. In Journal of Hydrology and Hydromechanics, vol. 67, no.4, pp. 314-321. 0042-790X (until 2019) . DOI: https://doi.org/10.2478/johh-2019-0021
APA:
Kozel, T., Stary, M. (2019). Adaptive stochastic management of the storage function for a large open
reservoir using an artificial intelligence method. Journal of Hydrology and Hydromechanics, 67(4), 314-321. 0042-790X (until 2019) . DOI: https://doi.org/10.2478/johh-2019-0021
About edition:
Publisher: VEDA, Publishing House of the Slovak Academy of Sciences, Bratislava, Slovakia
Published: 15. 12. 2019