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A genetic programming approach to forecast daily electricity demand
(Springer Nature Switzerland AG, 2019)
A number of recent researches have compared machine learning techniques to find more reliable approaches to solve variety of engineering problems. In the present study, capability of canonical genetic programming (GP) ...
An improved gene expression programming model for streamflow forecasting in intermittent streams
(Elsevier, 2018)
Skilful forecasting of monthly streamflow in intermittent rivers is a challenging task in stochastic hydrology. In this study, genetic algorithm (GA) was combined with gene expression programming (GEP) as a new hybrid model ...
A novel fuzzy random forest model for meteorological drought classification and prediction in ungauged catchments
(Pure and Applied Geophysics, 2020)
This paper presents a new tree-based model, namely Fuzzy Random Forest (FRF), for one month ahead Standardized Precipitation Evapotranspiration Index (SPEI) classification and prediction with a noteworthy application in ...
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 ...
Multigene genetic programming for sediment transport modeling in sewers for conditions of non-deposition with a bed deposit
(Elsevier, 2018)
It is known that construction of large sewers based on consideration of flow with non-deposition without a bed deposit is not economical. Sewer design based on consideration of flow with non-deposition with a bed deposit ...
Climate change impacts on meteorological drought using SPI and SPEI: case study of Ankara, Turkey
(Hydrological Sciences Journal, 2019)
Using regionally downscaled and adjusted outputs of three global climate models (GCMs), meteorological drought analysis was accomplished across Ankara, the capital city of Turkey. To this end, standardized precipitation ...
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 ...
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 ...
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 ...
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 ...