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Toplam kayıt 18, listelenen: 1-10
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.
Experimental analysis for self-cleansing open channel design
(Journal of Hydraulic Research, 2020)
Self-cleansing is a hydraulic design concept for drainage systems for mitigation of sediment deposition. Experimental studies in the literature have mostly been performed in circular channels. In this study, experiments ...
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 ...
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 ...
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 ...
Urmia lake water depth modeling using extreme learning machine-improved grey wolf optimizer hybrid algorithm
(Springer, 2021)
Lake water level changes are relatively sensitive to the climate-born events that rely on numerous phenomena, e.g., surface soil type, adjacent groundwater discharge, and hydrogeological situations. By incorporating the ...
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 ...
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 ...
Hybrid models for suspended sediment prediction: optimized random forest and multi-layer perceptron through genetic algorithm and stochastic gradient descent methods
(Springer, 2021)
Owing to the nonlinear and non-stationary nature of the suspended sediment transport in rivers, suspended sediment concentration (SSC) modeling is a challenging task in environmental engineering. Investigation of SSC is ...
Sediment transport modeling in non-deposition with clean bed condition using different tree-based algorithms
(Public Library of Science, 2021)
To reduce the problem of sedimentation in open channels, calculating flow velocity is critical. Undesirable operating costs arise due to sedimentation problems. To overcome these problems, the development of machine learning ...