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Toplam kayıt 5, listelenen: 1-5
A hybrid support vector regression-firefly model for monthly rainfall forecasting
(Springer Berlin Heidelberg, 2019)
Long-term prediction of rainfalls is one of the most challenging tasks in stochastic hydrology owing to the highly random characteristics of rainfall events. In this paper, a novel approach is adopted to develop a hybrid ...
Pareto-optimal MPSA-MGGP: a new gene-annealing model for monthly rainfall forecasting
(Elsevier, 2019)
Rainfall is considered the hardest weather variable to forecast, and its cause-effect relationships often cannot be expressed in simple or complex mathematical forms. This study introduces a novel hybrid model to month ...
Genetic programming in water resources engineering: a state-of-the-art review
(Elsevier, 2018)
The state-of-the-art genetic programming (GP) method is an evolutionary algorithm for automatic generation of computer programs. In recent decades, GP has been frequently applied on various kind of engineering problems and ...
Trend analysis of hydroclimatological variables in Urmia lake basin using hybrid wavelet Mann–Kendall and Şen tests
(Springer-Verlag, 2018)
This paper investigates monthly, seasonal, and annual trends in rainfall, streamflow, temperature, and humidity amounts at Urmia lake (UL) basin and analyzes the interaction between these variables and UL’s water level ...
Season algorithm-multigene genetic programming: a new approach for rainfall-runoff modelling
(Springer Netherlands, 2018)
Genetic programming (GP) is recognized as a robust machine learning method for rainfall-runoff modelling. However, it may produce lagged forecasts if autocorrelation feature of runoff series is not taken carefully into ...