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An ensemble genetic programming approach to develop incipient sediment motion models in rectangular channels
(ELSEVIER, 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 ... -
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
(ASCE-AMER SOC CIVIL ENGINEERS, 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 ... -
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 ... -
Clear-water scour depth prediction in long channel contractions: Application of new hybrid machine learning algorithms
(2021)Scour depth prediction and its prevention is one of the most important issues in channel and waterway design. However the potential for advanced machine learning (ML) algorithms to provide models of scour depth has yet to ... -
Closure to the discussion of Ebtehaj et al. on "Comparative assessment of time series and artificial intelligence models to estimate monthly streamflow: A local and external data analysis approach"
(Elsevier, 2021)In this closure, we respond to the comments of Ebtehaj et al. (2020), and also provide additional details regarding several features of our study. -
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. ... -
Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes
(IRTCES, 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. ... -
Comparative assessment of time series and artificial intelligence models to estimate monthly streamflow: A local and external data analysis approach
(Journal of Hydrology, 2019)River flow rates are important for water resources projects. Given this, the current study explored the use of autoregressive (AR) and moving average (MA) techniques as individual time series models and compared them to ... -
Comparative assessment of time series and artificial intelligence models to estimate monthly streamflow: A local and external data analysis approach
(ELSEVIER, 2019)River flow rates are important for water resources projects. Given this, the current study explored the use of autoregressive (AR) and moving average (MA) techniques as individual time series models and compared them to ... -
Decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) models for sediment transport in sewer pipes
(IWA PUBLISHING, 2019)Sediment deposition in sewers and urban drainage systems has great effect on the hydraulic capacity of the channel. In this respect, the self-cleansing concept has been widely used for sewers and urban drainage systems ... -
Decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) models for sediment transport in sewer pipes
(Water Science and Technology, 2019)Sediment deposition in sewers and urban drainage systems has great effect on the hydraulic capacity of the channel. In this respect, the self-cleansing concept has been widely used for sewers and urban drainage systems ... -
Developing novel hybrid models for estimation of daily soil temperature at various depths
(ELSEVIER, 2020)Estimation of soil temperature (ST) as one of the vital parameters of soil, which has an impact on many chemical and physical characteristics of soil, is of great importance in soil science. This study applies a time ... -
Developing novel hybrid models for estimation of daily soil temperature at various depths
(Soil and Tillage Research, 2020)Estimation of soil temperature (ST) as one of the vital parameters of soil, which has an impact on many chemical and physical characteristics of soil, is of great importance in soil science. This study applies a time ... -
Discharge coefficient for vertical sluice gate under submerged condition using contraction and energy loss coefficients
(Elsevier, 2021)A novel method is suggested for the determination of flow discharge in vertical sluice gates with considerably small bias. First, in order to derive an equation for the discharge coefficient, energy-momentum equations are ... -
Drought modeling using classic time series and hybrid wavelet-gene expression programming models
(ELSEVIER, 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 ... -
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 ... -
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 ... -
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 ... -
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 ...
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