Evaluation of the least square support vector machines (LS-SVM) to predict longitudinal dispersion coefficient

Evaluation of the least square support vector machines (LS-SVM) to predict longitudinal dispersion coefficient

In this study, the least square support vector machines (LS-SVM) method was used to predict the longitudinal dispersion coefficient (DL) in natural streams in comparison with the empirical equations in various datasets. To do this, three datasets of field data including hydraulic and geometrical cha...

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Bibliographic Details
Main Authors: Mehdi Mohammadi Ghaleni, Mahmood Akbari, Saeed Sharafi, Mohammad Javad Nahvinia
Format: Article
Language:English
Published: IWA Publishing 2022-05-01
Series:Water Supply
Subjects:
empirical equations
least square support vector machines
longitudinal dispersion coefficients
natural streams
performance
Online Access:http://ws.iwaponline.com/content/22/5/5448

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http://ws.iwaponline.com/content/22/5/5448

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