Integration of advanced optimization algorithms into least-square support vector machine (LSSVM) for water quality index prediction

Machine learning models hybridized with optimization algorithms have been applied to many real-life applications, including the prediction of water quality. However, the emergence of newly developed advanced algorithms can provide new scopes and possibilities for further enhancements. In this study,...

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Veröffentlicht in:	Water science & technology. Water supply Jg. 22; H. 2; S. 1951 - 1963
Hauptverfasser:	Chia, See Leng, Chia, Min Yan, Koo, Chai Hoon, Huang, Yuk Feng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London IWA Publishing 01.02.2022
Schlagworte:	advanced optimization algorithm Algorithms Chemical oxygen demand Genetic algorithms hybrid optimized lssvm model kernel function Kernel functions Lagrange multiplier Least squares Machine learning Mutation Optimization algorithms Particle swarm optimization Predictions river water quality parameter Rivers Root-mean-square errors Support vector machines Water quality water quality index Selangor Malaysia Malaysia
ISSN:	1606-9749, 1607-0798
Online-Zugang:	Volltext
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