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Toplam kayıt 25, listelenen: 11-20
Self-cleansing design of sewers: Definition of the optimum deposited bed thickness
(Water Environment Research, 2019)
Sediment deposits may influence the performance of the sewer systems. Sediments are the main store of pollutants which causes sewer systems overflows. In order to prevent the deposition of sediment in sewer 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 ...
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 ...
Weighted instances handler wrapper and rotation forest-based hybrid algorithms for sediment transport modeling
(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 ...
Invasive weed optimization-based adaptive neuro-fuzzy inference system hybrid model for sediment transport with a bed deposit
(Journal of Cleaner Production, 2020)
Inasmuch as channels are designed to mitigate continues sedimentation, sediment transport models have been developed to calculate flow velocity to keep sediment particles in motion. In order to promote the computation ...
Hybridization of multivariate adaptive regression splines and random forest models with an empirical equation for sediment deposition prediction in open channel flow
(Journal of Hydrology, 2020)
It has been known that the channel cross-section shape impacts on flow velocity at sediment deposition condition; however, existing models only apply to specific cross-section shapes and there has been a lack of a general ...