Skip to main content
Have a personal or library account? Click to login
A stochastic approach to the operative control of flood flows through a reservoir Cover

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

Journal of Hydrology and Hydromechanics
Volume 64 (2016): Issue 1 (March 2016)
By: ,   and    
Open Access
|Jan 2016
References

References

  1. Březková, L., Starý, M., 2013. The stochastic discharge forecast – creation, interpretation and other applications. In: Chavoshian, A., Takeuchi, K. (Eds.): Floods - From Risk to Opportunity. IAHS Publ. 357. International Association of Hydrological Sciences, Centre for Ecology and Hydrology, Wallingford, Oxfordshire, OX10 8BB, UK.
    Search in Google Scholar
  2. Butcher, W.S., 1971. Stochastic dynamic programming for optimum reservoir operation. JAWRA Journal of the American Water Resources Association, 7, 115–123.
    Open DOISearch in Google Scholar
  3. Chandramouli, S., Nanduri, U.V., 2011. Comparison of stochastic and fuzzy dynamic programming models for the operation of a multipurpose reservoir. Water and Environment Journal, 25, 547–554.
    Open DOISearch in Google Scholar
  4. Chang, L.-C., Chang, F.-J., 2001. Intelligent control for modeling of real-time reservoir operation. Hydrological Processes, 15, 1621–1634.
    Open DOISearch in Google Scholar
  5. Chang, Y.-T., Chang, L.-C., Chang, F.-J., 2005. Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves. Hydrological Processes, 19, 1431–1444.
    Open DOISearch in Google Scholar
  6. Chang, L.-C., Chang, F.-J., Hsu, H.-C., 2011. Real-time reservoir operation for flood control using artificial intelligent techniques. International Journal of Nonlinear Sciences and Numerical Simulation, 11, 11, 887–902.
    Open DOISearch in Google Scholar
  7. Chaves, P., Tsukatani, T., Kojiri, T., 2004. Operation of storage reservoir for water quality by using optimization and artificial intelligence techniques. Mathematics and Computers in Simulation, 67, 4–5, 419–432.
    Open DOISearch in Google Scholar
  8. Drbal, K., 1999. Flood flow operative control by fuzzy regulation in lower part of water management system. (PhD Thesis). Brno University of Technology. Brno. 96 p.
    Search in Google Scholar
  9. Dubrovin, T., Jolma, A., Turunen, E., 2002. Fuzzy model for real-time reservoir operation. Journal Water Resources Planning Management, 128, 1, 66–73.
    Open DOISearch in Google Scholar
  10. Dupačová, J., Lachout, P., 2006. Introduction to the Optimization. 1st ed. Matfyzpress, Prague, 70 p. ISBN 80-246-0872-3.
    Search in Google Scholar
  11. Fošumpaur, P., Nacházel, K., Patera, A., 2002. Operative control decision model of flood discharge from reservoir. Journal of Hydrology and Hydromechanics, 50, 1, 29–49.
    Search in Google Scholar
  12. Jaroš, L., 2010. Use of artificial intelligence methods during operative control of flood flow by reservoir. (PhD Thesis). Brno University of Technology, Brno, 186 p.
    Search in Google Scholar
  13. Nacházel, K., Patera, A., Hejzlar, J., 1999. Control fuzzy model of water quality in reservoir. 1. part – Problem development and methodology of the research. Journal of Hydrology and Hydromechanics, 47, 3, 153–179.
    Search in Google Scholar
  14. Nacházel, K., Starý, M., Zezulák, J., 2004. Using of Artificial Inteligence Methods in Water Management. 1st ed. Academia, Prague, 319 p. ISBN 80-200-0229-4.
    Search in Google Scholar
  15. Starý, M., 1990. Reservoirs and Water Management Systems. Brno University of Technology, Faculty of Civil Engineering, Brno, 165 p. ISBN 80-214-0191-5.
    Search in Google Scholar
  16. Starý, M., 1991–2015. HYDROG. Software for simulation, prediction and operative control of water outflow from catchment area. HySoft, Brno.
    Search in Google Scholar
  17. Starý, M., 2001. Use of fuzzy regulator during operative control of single reservoir during the flood passage. In: 9th International Poster Day. Institute of Hydrology SAS, Bratislava, 7 p.
    Search in Google Scholar
  18. Starý, M., Doležal, P., 2004. Operative control of outflows from Dyjsko-svratecký system of reservoirs during the flood passage using the Fuzzy regulator. In: WORKSHOP 2004, Prague. Czech Technical University in Prague, Faculty of Civil Engineering, Prague, pp. 54–58.
    Search in Google Scholar
  19. The Mathworks, 1984–2012. The Language of Technical Computing. Mathworks, Natick, MA.
    Search in Google Scholar
DOI: https://doi.org/10.1515/johh-2016-0012 | Journal eISSN: 1338-4333 (formerly 0042-790X) | Journal ISSN: 0042-790X
Journal RSS Feed
Language: English
Page range: 91 - 96
Submitted on: Aug 14, 2015
Accepted on: Dec 1, 2015
Published on: Jan 26, 2016
Published by: Slovak Academy of Sciences, Institute of Hydrology
In partnership with: Paradigm Publishing Services
Keywords:
Operative control of reservoir,
Artificial intelligence,
Fuzzy inference system,
Neural networks,
Stochastic forecast,
Stochastic control of reservoir,
Principle of adaptation
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2016 Lubomír Jaroš, Miloš Starý, Lucie Březková, published by Slovak Academy of Sciences, Institute of Hydrology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 64 (2016): Issue 1 (March 2016)
Previous article