NDLI: An expert system with radial basis function neural network based on decision trees for predicting sediment transport in sewers.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Ebtehaj, Isa Bonakdari, Hossein Zaji, Amir Hossein
Description	Author Affiliation: Ebtehaj I ( Department of Civil Engineering, Razi University, Kermanshah, Iran and Water and Wastewater Research Center, Razi University, Kermanshah, Iran E-mail: bonakdari@yahoo.com.); Bonakdari H ( Department of Civil Engineering, Razi University, Kermanshah, Iran and Water and Wastewater Research Center, Razi University, Kermanshah, Iran E-mail: bonakdari@yahoo.com.); Zaji AH ( Department of Civil Engineering, Razi University, Kermanshah, Iran and Water and Wastewater Research Center, Razi University, Kermanshah, Iran E-mail: bonakdari@yahoo.com.)
Abstract	In this study, an expert system with a radial basis function neural network (RBF-NN) based on decision trees (DT) is designed to predict sediment transport in sewer pipes at the limit of deposition. First, sensitivity analysis is carried out to investigate the effect of each parameter on predicting the densimetric Froude number (Fr). The results indicate that utilizing the ratio of the median particle diameter to pipe diameter (d/D), ratio of median particle diameter to hydraulic radius (d/R) and volumetric sediment concentration (C(V)) as the input combination leads to the best Fr prediction. Subsequently, the new hybrid DT-RBF method is presented. The results of DT-RBF are compared with RBF and RBF-particle swarm optimization (PSO), which uses PSO for RBF training. It appears that DT-RBF is more accurate (R(2) = 0.934, MARE = 0.103, RMSE = 0.527, SI = 0.13, BIAS = -0.071) than the two other RBF methods. Moreover, the proposed DT-RBF model offers explicit expressions for use by practicing engineers.
File Format	HTM / HTML
ISSN	02731223
Issue Number	1
Journal	Water Science & Technology
Volume Number	74
e-ISSN	19969732
Language	English
Publisher	IWA Publishing
Publisher Date	2016-01-01
Publisher Place	Great Britain (UK)
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article
Subject	Environmental Engineering Water Science and Technology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in