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Open image in new window Fig. 13 Calibration of spread foundation: a Calibration model.
Open image in new window Fig. 12 Ground parameters calibration: a Calibration model.
Accuracy of the proposed method was tested using images of a calibration model.
A calibration model was developed using partial least squares regression (PLSR).
In this work, in order to perform an in vitro assessment of the method, a calibration model was designed.
In this application, partial least squares regression was used with Karl Fischer volumetric titration analysis to generate a calibration model.
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Each compound was calibrated with a linear calibration model with a 9-point correlation coefficient (R) of 0.99 or better.
Choosing a useful calibration model is a complex optimisation problem which can be solved by experimental designs.
The question was whether a useful calibration model could be built with a limited number of samples.
A new calibration model by formulating the calibration problem as a multi-objective optimization problem is presented.
Leave one out cross validation [29] is a commonly used algorithm for estimating predictive performance of a multivariable calibration model.
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