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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 ...
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. ...
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 ...
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 ...
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 ...
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 ...
Pipe failure rate prediction in water distribution networks using multivariate adaptive regression splines and random forest techniques
(Urban Water Journal, 2019)
This paper presents the results of a comparison between multivariate adaptive regression splines (MARS) and random forest (RF) techniques in pipe failure prediction in two water distribution networks. In this regard, pipe ...
Sediment transport modeling in rigid boundary open channels using generalize structure of group method of data handling
(Journal of Hydrology, 2019)
Sediment transport in open channels has complicated nature and finding the analytical models applicable for channel design in practice is a quite difficult task. To this end, behind theoretical consideration of the open ...
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 ...
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. ...