NDLI: Estimation of Scour Downstream of a Ski-Jump Bucket Using Support Vector and M5 Model Tree

Content Provider	Springer Nature Link
Author	Goyal, Manish Kumar Ojha, C. S. P.
Copyright Year	2011
Abstract	Estimation of scour downstream of a ski-jump bucket has been a topic of research among hydraulic engineers. For estimation of scour downstream of ski jump bucket, several empirical models are in use. In recent years, there has been emphasis to develop models which are capable of producing scour with high accuracy. Use of Artificial Neural Network (ANN) approach to model depth, width and length of scour hole indicates that performance of ANN models is far better than existing empirical models. At present, use of Support Vector Machines (SVMs) and M5 Pruned Model Tree are being considered in different disciplines to further improve upon the performance of ANN models as a potential alternate. With this in view, the present study deals with the development of regression models for computing various parameters of scour hole using SVMs and M5 Model Tree. A comparative evaluation of the performance of ANN versus SVMs and M5 Model Tree clearly shows that SVMs and M5 Model Tree can prove more useful than ANN models in estimation of scour downstream of a ski jump bucket. Further, M5 model tree offers explicit expressions for use by design engineers.
Starting Page	2177
Ending Page	2195
Page Count	19
File Format	PDF
ISSN	09204741
Journal	Water Resources Management
Volume Number	25
Issue Number	9
e-ISSN	15731650
Language	English
Publisher	Springer Netherlands
Publisher Date	2011-03-11
Publisher Institution	European Water Resources Association (EWRA)
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	ANN M5 Scour Ski-Jump Bucket SVMs Hydraulics Prediction Meteorology/Climatology Hydrogeology Environment Civil Engineering Geotechnical Engineering
Content Type	Text
Resource Type	Article
Subject	Water Science and Technology Civil and Structural Engineering

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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
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