A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems

A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems

Sediment is a universal issue that generated in the river catchment and affects the river flow, reservoir capacity, hydropower generation and dam structure. This paper aims to present the result of experimentation in sediment load estimation using various machine learning algorithms as a powerful AI...

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Bibliographic Details
Main Authors: Gasim Hayder, Mahmud Iwan Solihin, Khairul Faizal Bin Kushiar
Format: Article
Language:English
Published: Polish Society of Ecological Engineering (PTIE) 2021-07-01
Series:Journal of Ecological Engineering
Subjects:
river systems
artificial intelligence
sediment estimation
machine learning prediction
visual programming
hydro-informatics systems
Online Access:http://www.jeeng.net/A-Performance-Comparison-of-Various-Artificial-Intelligence-Approaches-for-Estimation,137847,0,2.html

Internet

http://www.jeeng.net/A-Performance-Comparison-of-Various-Artificial-Intelligence-Approaches-for-Estimation,137847,0,2.html

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