The potential of FFNN and MLP-FFA approaches in prediction of Manning coefficient in ripple and dune bedforms

The potential of FFNN and MLP-FFA approaches in prediction of Manning coefficient in ripple and dune bedforms

An accurate prediction of roughness coefficient is of substantial importance for river management. The current study applies two artificial intelligence methods namely; Feed-Forward Neural Network (FFNN) and Multilayer Perceptron Firefly Algorithm (MLP-FFA) to predict the Manning roughness coefficie...

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Bibliographic Details
Main Authors: Vahid Abdi, Seyed Mahdi Saghebian
Format: Article
Language:English
Published: IWA Publishing 2021-11-01
Series:Water Supply
Subjects:
alluvial channel
bedforms
flow resistance
intelligence methods
multilayer perceptron firefly algorithm
Online Access:http://ws.iwaponline.com/content/21/7/3900

Internet

http://ws.iwaponline.com/content/21/7/3900

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