Estimation of settling velocity using generalized reduced gradient (GRG) and hybrid generalized reduced gradient–genetic algorithm (hybrid GRG-GA)

This study describes the settling velocity phenomenon and deals with the methods for its estimation. The accuracy of three previously proposed settling velocity equations is also checked in this study. After graphical and statistical analysis, the authors proposed generalized reduced gradient (GRG)...

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Vydáno v:	Acta geophysica Ročník 70; číslo 5; s. 2487 - 2497
Hlavní autoři:	Shivashankar, M., Pandey, Manish, Zakwan, Mohammad
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.10.2022
Témata:	Earth and Environmental Science Earth Sciences Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Research Article - Special Issue Structural Geology Settling velocity Sediment Hybrid GRG-GA
ISSN:	1895-7455, 1895-7455
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Abstract	This study describes the settling velocity phenomenon and deals with the methods for its estimation. The accuracy of three previously proposed settling velocity equations is also checked in this study. After graphical and statistical analysis, the authors proposed generalized reduced gradient (GRG) and hybrid generalized reduced gradient–genetic algorithm (hybrid GRG-GA) approaches for the estimation of settling velocity. Hybrid GRG-GA-based settling velocity approach showed more precise results than GRG approach. In addition, hybrid GRG-GA and GRG approaches were compared with previously proposed equations using 226 data points. The graphical and statistical analysis shows that the hybrid GRG-GA and GRG approaches give better agreement with observed data points as compared to previously proposed equations. Application of hybrid GRG-GA reduces the sum of square of error in fall velocity by over 70% and 30% on an average as compared to previous equations during training and testing, respectively. This study highlights that the hybrid GRG-GA approach could be efficiently used for calculating the settling velocity.
AbstractList	This study describes the settling velocity phenomenon and deals with the methods for its estimation. The accuracy of three previously proposed settling velocity equations is also checked in this study. After graphical and statistical analysis, the authors proposed generalized reduced gradient (GRG) and hybrid generalized reduced gradient–genetic algorithm (hybrid GRG-GA) approaches for the estimation of settling velocity. Hybrid GRG-GA-based settling velocity approach showed more precise results than GRG approach. In addition, hybrid GRG-GA and GRG approaches were compared with previously proposed equations using 226 data points. The graphical and statistical analysis shows that the hybrid GRG-GA and GRG approaches give better agreement with observed data points as compared to previously proposed equations. Application of hybrid GRG-GA reduces the sum of square of error in fall velocity by over 70% and 30% on an average as compared to previous equations during training and testing, respectively. This study highlights that the hybrid GRG-GA approach could be efficiently used for calculating the settling velocity.
Author	Zakwan, Mohammad Shivashankar, M. Pandey, Manish
Author_xml	– sequence: 1 givenname: M. surname: Shivashankar fullname: Shivashankar, M. organization: Water Resources and Environmental Div., Civil Engineering Department, NIT Warangal – sequence: 2 givenname: Manish orcidid: 0000-0002-4215-5671 surname: Pandey fullname: Pandey, Manish email: manishpandey3aug@gmail.com, mpandey@nitw.ac.in organization: Water Resources and Environmental Div., Civil Engineering Department, NIT Warangal – sequence: 3 givenname: Mohammad surname: Zakwan fullname: Zakwan, Mohammad organization: Department of Civil Engineering, MANUU
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Snippet	This study describes the settling velocity phenomenon and deals with the methods for its estimation. The accuracy of three previously proposed settling...
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Title	Estimation of settling velocity using generalized reduced gradient (GRG) and hybrid generalized reduced gradient–genetic algorithm (hybrid GRG-GA)
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