2020
DOI: 10.1007/s00128-020-02803-2
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Linear and Nonlinear Isotherm Models and Error Analysis for the Sorption of Kresoxim-Methyl in Agricultural Soils of India

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Cited by 39 publications
(20 citation statements)
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“…Though non-linear approach to error assessment is complex and sophisticated, it restrains errors which would have occurred through linearization of the nonlinear error [30]. The fit of the selected isotherms to the experimental adsorption data were evaluated through optimization of the selected error functions.…”
Section: Nonlinear Error Functions Analysismentioning
confidence: 99%
“…Though non-linear approach to error assessment is complex and sophisticated, it restrains errors which would have occurred through linearization of the nonlinear error [30]. The fit of the selected isotherms to the experimental adsorption data were evaluated through optimization of the selected error functions.…”
Section: Nonlinear Error Functions Analysismentioning
confidence: 99%
“…The error values show the variation between the predicted and the experimental data. The lower error values were obtained with nonlinear models compered to linear models which is indicating that the errors were introduced while linearizing the adsorption data 38 . It was clear that both isotherm models have a higher correlation factor and lower error function values, suggesting that both isotherms are better.…”
Section: Resultsmentioning
confidence: 88%
“…An error function is usually defined to search for the best fit isotherm and kinetic model that satisfies the experimental adsorption data. Five Error function are used to evaluate the models by using the EXCEL FUNCTION and Origin Pro8.5 36–38 . They are residual mean square error (RMSE), chi‐square (χ2), The sum of the squares of the errors (ERRSQ), average relative error (ARE), and hybrid fractional error (HYBRID).…”
Section: Methodsmentioning
confidence: 99%
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