• DocumentCode
    183089
  • Title

    Data mining in hydrological domain

  • Author

    Krammer, Peter ; Habala, Ondrej ; Hluchy, Ladislav ; Tothova, Katarina

  • Author_Institution
    Inst. of Inf., Bratislava, Slovakia
  • fYear
    2014
  • fDate
    19-21 Aug. 2014
  • Firstpage
    725
  • Lastpage
    728
  • Abstract
    Hydrological domain provides several interesting tasks with strong practical applications. The domain also generates broad data set, which contains patterns or relations. But the data set contains errors with significant stochastic characteristics; So, the data mining techniques with statistical approach are excellent tools for hydrological tasks solving. Presented paper is focused on water consumption modelling and prediction, which could be applied in several tasks, for example in hydrological scheduling system.
  • Keywords
    data mining; geophysics computing; hydrology; stochastic processes; data mining; data set; hydrological domain; hydrological scheduling system; hydrological tasks solving; statistical approach; stochastic characteristics; water consumption modelling; water consumption prediction; Data mining; Numerical models; Predictive models; Regression tree analysis; Reservoirs; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4799-5147-5
  • Type

    conf

  • DOI
    10.1109/FSKD.2014.6980925
  • Filename
    6980925