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Electrical Energy Demand Prediction: A Comparison Between Genetic Programming and Decision Tree
(GAZI UNIV, 2020)
Several recent studies have used various data mining techniques to obtain accurate electrical energy demand forecasts in power supply systems. This paper, for the first time, compares the efficiency of the decision tree ...
Drought modeling using classic time series and hybrid wavelet-gene expression programming models
(Journal of Hydrology, 2020)
The standardized precipitation evapotranspiration index (SPEI) at three different time scales (i.e., SPEI-3, SPEI-6, and SPEI-12) from six meteorology stations located in Turkey are modeled in this study. To this end, two ...
Rainfall-runoff modeling through regression in the reproducing kernel Hilbert space algorithm
(Journal of Hydrology, 2020)
In this study, Regression in the Reproducing Kernel Hilbert Space (RRKHS) technique which is a non-linear regression approach formulated in the reproducing kernel Hilbert space (RRKHS) is applied for rainfall-runoff (R-R) ...
An ensemble genetic programming approach to develop incipient sediment motion models in rectangular channels
(Journal of Hydrology, 2020)
Assimilating unique features of genetic programming (GP) and gene expression programming (GEP), this study introduces a hybrid algorithm which results in promising incipient non-cohesive sediment motion models. The new ...
Application of Soft Computing Techniques for Particle Froude Number Estimation in Sewer Pipes
(Journal of Pipeline Systems Engineering and Practice, 2020)
Sedimentation in sewer networks is a major problem in urban hydrology. In comparison to the well-known classic sediment transport models, this study investigates the capabilities of soft computing methods, including multigene ...
Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes
(International Journal of Sediment Research, 2020)
Mitigation of sediment deposition in lined open channels is an essential issue in hydraulic engineering practice. Hence, the limiting velocity should be determined to keep the channel bottom clean from sediment deposits. ...
Electrical energy demand prediction: A comparison between genetic programming and decision tree
(Gazi University Journal of Science, 2020)
Several recent studies have used various data mining techniques to obtain accurate electrical energy demand forecasts in power supply systems. This paper, for the first time, compares the efficiency of the decision tree ...
Multiple genetic programming: a new approach to improve genetic-based month ahead rainfall forecasts
(Environmental Monitoring and Assessment, 2020)
It is well documented that standalone machine learning methods are not suitable for rainfall forecasting in long lead-time horizons. The task is more difficult in arid and semiarid regions. Addressing these issues, the ...
Electrical Energy Demand Prediction: A Comparison Between Genetic Programming And Decision Tree
(2020)
Several recent studies have used various data mining techniques to obtain accurate electrical energy demand forecasts in power supply systems. This paper, for the first time, compares the efficiency of the decision tree ...