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Moreover, predictions of the HFO refrigerants viscosities showed lower deviations than ECS.
However, large deviations in the final product purities are seen with three-point control giving comparatively lower deviations.
The TZVPD-FINE parameterization did not yield significantly lower deviations from the experimental values than TZVP, while calculations with the latter were up to ten times faster.
The lower deviations were achieved by two models of Vaz Magalhães Silva (2.50% and 3.56%), He Yu Su equation (4.20%), Catchpole King correlation (4.94%), and Wilke Chang equation (5.34%).
The results showed that the proposed method to estimate the thermal conductivity of ionic liquids at different temperatures and pressures presented a good accuracy with lower deviations such as AARD less than 0.91% and R2 of 0.9969 for the training set, and AARD less than 0.84% with R2 of 0.9963 for the prediction set.
For all delineation methods, the deviation of MTV was comparable, where the adaptive threshold method resulted in slightly lower deviations for CT5 and the fixed threshold method showed slightly lower deviations for CT1 (see Figure 3).
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The developed correlation gives lower deviation from the experimental data than the well-known correlation of Whittle and Forgan.
The process performances such as upper deviation (Yuw), lower deviation (Ylw) and depth (Yd) characteristics of laser-turned micro-grooves produced on cylindrical work piece made of Al2O3 were evaluated.
From the analysis, it was found that proper control of the process parameters lead to achieve minimum upper deviation, lower deviation and depth of laser-turned micro-grooves produced on cylindrical workpiece of Al2O3.
In addition, the comparisons of single-objective and double-objective optimization approaches clearly show that multi-objective optimization methods yield more appropriate results respect to the single ones, mainly because of the lower deviation index value from the ideal solution.
The comparisons of triple-objective and dual-objective optimization with single-objective optimization indicate that multi-objective optimization can yield the more suitable results due to the lower deviation index from the ideal solution.
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