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We present the formal structure of the model, the calibration procedure and the data sources for calibrating the model and estimating the trade cost reductions stemming from new transport links.
In order to compare the OPLS-ANN model, the calibration models that using first-derivative and second-derivative preprocessing spectra were also designed.
In order to compare with O-PLS-ANN model, the calibration models that use the original spectra and different preprocessing methods (first-derivative, second-derivative, standard normal variate (SNV) and multiplicative scatter correction (MSC)) of the spectra were also designed.
With respect to the second tour time-of-day choice model the calibration results, consistently with the observed data, show that the workers who choose to carry out a second tour with non-work activities (H-W-H-L-H, H-W-H-P/D-H, H-W-H-O-H) prefer the third timeframe (17 30 20 00/17 30 20 00), probably more suitable for carrying out such activities.
To assess the predictive performance of the model, the calibration and discrimination were computed in the validation group.
These unobserved parameters were linked to observed outcomes via the CRC natural history model, the calibration methods searched over possible parameter values, and selected those which best fit the observed data.
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Unlike existing calibration models, the proposed model makes the calibration problem well-posed.
One of the issues associated with such models is the calibration of model coefficients.
The new model requires the calibration of fewer cultivar specific parameters than either of the parent models, making cultivar calibration simpler.
We also consider issues when the model for the calibration function is only partially known.
PRESS values are indications of how closely a model fits the calibration data.
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