Title :
Data mining in hydrological domain
Author :
Krammer, Peter ; Habala, Ondrej ; Hluchy, Ladislav ; Tothova, Katarina
Author_Institution :
Inst. of Inf., Bratislava, Slovakia
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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5147-5
DOI :
10.1109/FSKD.2014.6980925
