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Moreover, when the unknown parameters are discrete (e.g., geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly.
Recent advances in sparse reconstruction, known as compressed sensing, have inspired efficient and flexible model calibration techniques that offer a departure from classical reduced-order parameterization techniques, where only prior knowledge is used to select the parameterization subspace.
The second issue is the largest obstacle facing model calibration techniques.
A natural history model of NSCLC was developed using incidence data, data elicited from clinical experts and model calibration techniques.
Therefore, in the absence of observable data, model calibration techniques (Weinstein, 2006; Whyte et al, 2011), together with the elicitation of clinical knowledge, were used to estimate the unobservable transition probabilities.
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Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological modeling framework based on a traditional Pareto-based model calibration technique.
In [26] a standard model calibration technique is introduced.
This paper addresses the subject of a new deterministic model calibration technique based on simulated annealing, which improves the model performance by means of a few pilot measurements.
To address a growing concern about the predictive capability of the computational models, this paper proposes a hierarchical model calibration procedure with a statistical model calibration technique.
For applications other than PIV, such as underwater photography and photogrammetry, several models and calibration techniques have been proposed to explicitly correct for the distortion due to a change of refractive media.
Thus, this approach offers higher accuracy than that of conventional global system model-based calibration technique.
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model calibration purposes
model adaptation techniques
model calibration results
model selection techniques
model calibration steps
model inversion techniques
model comparison techniques
model reduction techniques
model transformation techniques
model regression techniques
model evaluation techniques
model approximation techniques
model compensation techniques
model registration techniques
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