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Toplam kayıt 14, listelenen: 11-14
Hybrid models to improve the monthly river flow prediction: Integrating artificial intelligence and non-linear time series models
(Journal of Hydrology, 2019)
Prediction of river flow as a fundamental source of hydrological information plays a crucial role in various fields of water projects. In this study, at first, the capabilities of two time series analysis approaches, namely ...
Sediment transport modeling in open channels using neuro-fuzzy and gene expression programming techniques
(Water Science and Technology, 2019)
Deposition of sediment is a vital economical and technical problem for design of sewers, urban drainage, irrigation channels and, in general, rigid boundary channels. In order to confine continuous sediment deposition, ...
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 ...