Sediment transport modeling in open channels using neuro-fuzzy and gene expression programming techniques

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, rigid boundary channels are designed based on self-cleansing criteria. Recently,...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Water science and technology Jg. 79; H. 12; S. 2318 - 2327
Hauptverfasser: Kargar, Katayoun, Safari, Mir Jafar Sadegh, Mohammadi, Mirali, Samadianfard, Saeed
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England IWA Publishing 15.06.2019
Schlagworte:
Artificial neural networks
Channels
Deposition
Drainage channels
Empirical equations
Flow velocity
Fluid flow
Froude number
Fuzzy Logic
Gene Expression
Genetic algorithms
Geologic Sediments
Hydraulics
Hydrology
Load
Models, Chemical
Neural networks
Open channels
Optimization algorithms
Pipes
Regression models
Root-mean-square errors
Sediment
Sediment transport
Sedimentation & deposition
Sewer systems
Sewers
Shear stress
Statistical analysis
Transport
Urban drainage
United Kingdom > UK
ISSN:0273-1223, 1996-9732
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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, rigid boundary channels are designed based on self-cleansing criteria. Recently, instead of using a single velocity value for design of the self-cleansing channels, more hydraulic parameters such as sediment, fluid, flow and channel characteristics are being utilized. In this study, two techniques of neuro-fuzzy (NF) and gene expression programming (GEP) are implemented for particle Froude number estimation of the non-deposition condition of sediment transport in rigid boundary channels. The models are established based on laboratory experimental data with wide ranges of sediment and pipe sizes. The developed models' performances have been compared with empirical equations based on two statistical factors comprising the root mean square error (RMSE) and the concordance coefficient (CC). Besides, Taylor diagrams are used to test the resemblance between measured and calculated values. The outcomes disclose that NF4, as the precise NF model, performs better than the best GEP model (GEP1) and regression equations. As a conclusion, the obtained results proved the suitable accuracy and applicability of the NF method in estimation.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0273-1223
1996-9732
DOI:10.2166/wst.2019.229