The enhanced levels of accuracy obtained with the SVR combined with PCA based calibration models open up avenues for prospective prediction in coal properties.
The analysis allowed proposing an analytical model, based on the calibration of a theoretical model, correlating air permeability with resistance to carbonation.
The value of the parameters of Fig. 16 was found for model 'A', based on the calibration with the results of the respective experimental data.
A calibration model based on 52 samples collected over 4 days and employing two digital filters produces a standard error of calibration (SEC) of 0.36 mM glucose.
A modified analytical model based on test result calibration for the calculation of sectional properties is proposed for design reference.
The partial least squares (PLS-1) calibration model based on spectrophotometric measurement, for the simultaneous determination of CN− and SCN− ions is described.
Then, in the optimal experimental conditions of the extraction, MG and LMG have been determined by using a three-way calibration model based on parallel factor analysis (PARAFAC).
The partial least squares (PLS-1) calibration model based on spectrophotometric measurement for simultaneous determination of sulfite and sulfide ions was applied.
Studies using blends were performed to develop a NIR calibration model based on the feed frame system dynamics to determine acetaminophen drug concentration variability during the die filling process.
Solutions containing both metal ions in the concentration range from 1.0 to 4.0 mg L−1 were employed to constructed the calibration model based on multiple linear regression (MLR), providing root mean square errors of prediction of 0.06 and 0.12 mg L−1 for Zn II) and Cu II), respectively.
The comparison used the replicate data from the lower concentration standards prepared in low-retention plastic only, with a calibration model based only on standards from low-retention plastic.
