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On the Importance of Choosing the Best Minimization Algorithm for the Determination of Ternary Diffusion Coefficients by the Taylor Dispersion Method
[Image: see text] Taylor dispersion method is a common technique for the determination of diffusion coefficients in the case of multicomponent systems. One of the main problems related to the parameter estimation analysis of the collected results is the choice of the best minimization algorithm that...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6641195/ https://www.ncbi.nlm.nih.gov/pubmed/31457629 http://dx.doi.org/10.1021/acsomega.7b00384 |
Sumario: | [Image: see text] Taylor dispersion method is a common technique for the determination of diffusion coefficients in the case of multicomponent systems. One of the main problems related to the parameter estimation analysis of the collected results is the choice of the best minimization algorithm that allows finding the real minimum of the objective function. Usually, researchers use the Levenberg–Marquardt algorithm, averaging the parameters obtained by different estimation analyses. In this paper, some nonlinear minimization algorithms included in MATLAB R2016a have been tested, and the results are compared in terms of best fit on the experimental data collected for sodium dodecyl sulfate (SDS) + sodium octanoate (SOC) + water system. |
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