Yazar
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Clear-water scour depth prediction in long channel contractions: Application of new hybrid machine learning algorithms
Khosravi, K.; Safari, M.J.S.; Cooper, J.R. (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"
Mehdizadeh, S.; Fathian, F.; Safari, M.J.S.; Adamowski, J.F. (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. -
Discharge coefficient for vertical sluice gate under submerged condition using contraction and energy loss coefficients
Vaheddoost, B.; Safari, M.J.S.; Ilkhanipour Zeynali, R. (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 ... -
Hybrid models for suspended sediment prediction: optimized random forest and multi-layer perceptron through genetic algorithm and stochastic gradient descent methods
Safari, M.J.S. (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
Gul, E.; Safari, M.J.S.; Haghighi, A.T.; Mehr, A.D. (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 ... -
Urmia lake water depth modeling using extreme learning machine-improved grey wolf optimizer hybrid algorithm
Safari, M.J.S. (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 ... -
Weighted instances handler wrapper and rotation forest-based hybrid algorithms for sediment transport modeling
Kargar, K.; Safari, M.J.S.; Khosravi, K. (Elsevier, 2021-07)Sediment transport modeling has been known as an essential issue and challenging task in water resources and environmental engineering. In order to minimize the adverse impacts of the continues sediment deposition that is ...
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