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Purpose: To evaluate the capability of various kernels employed with support vector regression (SVR) and Gaussian process regression (GPR) techniques in estimating the volumetric oxygen transfer coefficient of plunging hollow jets. Design/methodology/approach: In this study, a data set of 81 observations is acquired from laboratory experiments of hollow jets plunging on the surface of water in the...
The aim of this paper to assesses the potential of machine learning approaches, i.e. multi-linear regression (MLR), support vector regression (SVR), Gaussian process (GP) regression of cumulative infiltration and compares their performances with three traditional models [Kostiakov model, US-Soil Conservation Service (SCS) model and Philip’s model]. Data set as many as 413 were obtained by conducting...
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