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Performance Evaluation of Adaptive Neural Fuzzy Inference System for Sediment Transport in Sewers
by
Ebtehaj, Isa
, Bonakdari, Hossein
in
Accuracy
/ Adaptive systems
/ Algorithms
/ Atmospheric Sciences
/ Back propagation
/ Civil Engineering
/ Dimensional analysis
/ Earth and Environmental Science
/ Earth Sciences
/ Earth, ocean, space
/ Engineering and environment geology. Geothermics
/ Environment
/ equations
/ Estimating techniques
/ Exact sciences and technology
/ Experiments
/ Flow resistance
/ Froude number
/ Fuzzy logic
/ Fuzzy sets
/ Geotechnical Engineering & Applied Earth Sciences
/ Hydrogeology
/ Hydrology. Hydrogeology
/ Hydrology/Water Resources
/ Inference
/ Mathematical analysis
/ Mathematical models
/ Methods
/ Neural networks
/ Performance evaluation
/ Pollution, environment geology
/ prediction
/ Sediment transport
/ Sedimentation & deposition
/ sediments
/ Sewer systems
/ Sewers
/ Studies
/ Time series
/ Water resources
/ Water resources management
2014
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Performance Evaluation of Adaptive Neural Fuzzy Inference System for Sediment Transport in Sewers
by
Ebtehaj, Isa
, Bonakdari, Hossein
in
Accuracy
/ Adaptive systems
/ Algorithms
/ Atmospheric Sciences
/ Back propagation
/ Civil Engineering
/ Dimensional analysis
/ Earth and Environmental Science
/ Earth Sciences
/ Earth, ocean, space
/ Engineering and environment geology. Geothermics
/ Environment
/ equations
/ Estimating techniques
/ Exact sciences and technology
/ Experiments
/ Flow resistance
/ Froude number
/ Fuzzy logic
/ Fuzzy sets
/ Geotechnical Engineering & Applied Earth Sciences
/ Hydrogeology
/ Hydrology. Hydrogeology
/ Hydrology/Water Resources
/ Inference
/ Mathematical analysis
/ Mathematical models
/ Methods
/ Neural networks
/ Performance evaluation
/ Pollution, environment geology
/ prediction
/ Sediment transport
/ Sedimentation & deposition
/ sediments
/ Sewer systems
/ Sewers
/ Studies
/ Time series
/ Water resources
/ Water resources management
2014
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Performance Evaluation of Adaptive Neural Fuzzy Inference System for Sediment Transport in Sewers
by
Ebtehaj, Isa
, Bonakdari, Hossein
in
Accuracy
/ Adaptive systems
/ Algorithms
/ Atmospheric Sciences
/ Back propagation
/ Civil Engineering
/ Dimensional analysis
/ Earth and Environmental Science
/ Earth Sciences
/ Earth, ocean, space
/ Engineering and environment geology. Geothermics
/ Environment
/ equations
/ Estimating techniques
/ Exact sciences and technology
/ Experiments
/ Flow resistance
/ Froude number
/ Fuzzy logic
/ Fuzzy sets
/ Geotechnical Engineering & Applied Earth Sciences
/ Hydrogeology
/ Hydrology. Hydrogeology
/ Hydrology/Water Resources
/ Inference
/ Mathematical analysis
/ Mathematical models
/ Methods
/ Neural networks
/ Performance evaluation
/ Pollution, environment geology
/ prediction
/ Sediment transport
/ Sedimentation & deposition
/ sediments
/ Sewer systems
/ Sewers
/ Studies
/ Time series
/ Water resources
/ Water resources management
2014
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Performance Evaluation of Adaptive Neural Fuzzy Inference System for Sediment Transport in Sewers
Journal Article
Performance Evaluation of Adaptive Neural Fuzzy Inference System for Sediment Transport in Sewers
2014
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Overview
The application of models capable of estimating sediment transport in sewers has been a frequent practice in the past years. Considering the fact that predicting sediment transport within the sewer is a complex phenomenon, the existing equations used for predicting densimetric Froude number do not present similar results. Using Adaptive Neural Fuzzy Inference System (ANFIS) this article studies sediment transport in sewers. For this purpose, five different dimensionless groups including motion, transport, sediment, transport mode and flow resistance are introduced first and then the effects of various parameters in different groups on the estimation of the densimetric Froude number in the motion group are presented as six different models. To present the models, two states of grid partitioning and sub-clustering were used in Fuzzy Inference System (FIS) generation. Moreover, the training algorithms applied in this article include back propagation and hybrid. The results of the proposed models are compared with the experimental data and the existing equations. The results show that ANFIS models have greater accuracy than the existing sediment transport equations.
Publisher
Springer-Verlag,Springer Netherlands,Springer,Springer Nature B.V
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