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Numerical experiments indicate that when the penetration rate of automated vehicles in the traffic stream is highly variable, the second order model based estimator offers improved accuracy compared to a scalar traffic flow model.
This paper presents a novel technique for the real time estimation of the wheel-rail contact forces based on an estimator design model that takes into account the nonlinearities of the interaction by means of a fitting model functional to reproduce the contact mechanics in a wide range of slip and to be easily integrated in a complete model based estimator for railway vehicle.
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A multi-model observer based estimator (OBE), which consists of a set of simple sub-models describing typical process states and a knowledge-based system, was developed for monitoring and long-term prediction of the anaerobic digestion process.
Model based variance estimator for the standard errors was used as recommended in the presence of few large clusters [ 26].
In recent years, the model based state estimators are welcomed widely, since they can adjust the gain according to the error between the model predictions and measurements timely.
This dynamic model based state estimators incorporate component balance equations together with thermodynamic relations, that include bubble point temperature computation and avoid constant relative volatility concept.
Both MCOIN and the E-values based estimator improve AUC by choosing models at shorter widths.
We estimated θ using the sample homozygoisty-based estimator developed by Xu and Fu (2004) [ 22], which is approximately unbiased under the single-step stepwise mutation model and has a much smaller variance than the size-variance based estimator.
The model based on fuzzy estimators supporting daily coordination plans, standard load curve model supporting monthly coordination plans and hybrid model supporting annual coordination plans are presented.
This inverse analysis is a surrogate model based on a Kriging estimator.
Wang et al. (2013) developed a cost estimator model based on NN.
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