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These models provide best fit to experimentally measured impedances and/or transient responses and employ one or more constant phase element (CPEs) [3]; also known as the fractional-order capacitor [4].
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The 1T2k60 and 2T4k models provided best fits in 1 (5%) and 2 (9%) out of 22 scans with mean AIC values of -81 ± 13 and -96 ± 14, respectively.
Langmuir isotherm, pseudo second order kinetic and ion exchange models provided best fit to the experimental data of sorption of metal ions.
For FBP reconstructed data, the 2T4kVTnsfix model provided best fits in 19 out of 22 scans (86%) according to the AIC with a mean value of -98 ± 13.
Analysis of the R 2 values suggests that the Langmuir isotherm model provides best fit to the equilibrium biosorption data at all studied temperatures implying monolayer coverage of CV molecules onto the biosorbent surface.
On comparing the pseudo-first order and the pseudo-second order adsorption rate constants at different initial metal concentrations, it is seen that the second-order model provides best correlation of the data.
If DMUs are taken from an infinite set, DEA models can provide best estimations of production frontier.
The AASHTO shear-friction and the SMCS models provide the best correlation with the experimental results.
On the other hand, the K-S distances corresponding to the exponential and gamma models are the smallest, implying that these two models provide the best fit.
For all the systems studied, the intraparticle diffusion model, pseudo first-order and pseudo second-order isotherm models provide the best correlation of the experimental data.
The goal of this contest is to discover which statistical and machine learning models provide the best predictions of daily-aggregated solar radiation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com