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The inference approach used is based on a GEV distribution and a Bayesian Monte Carlo Markov Chain approach for parameters estimation.
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The approach for parameter estimation is based on that in [11].
To achieve the goal, a model-based design of experiment (MBDOE) approach for parameter estimation is employed.
The paper presents a direct adaptive fuzzy approach for parameter identification and control of unknown nonlinear systems.
The proposed approach for parameter estimation is capable of estimating unknown parameters even away from the broadside of the beam pattern.
If an adequate probabilistic framework can be specified for a sample data set, maximum likelihood [ML] typically provides an efficient approach for parameter estimation.
Delpiano et al. [19], for instance, proposed a multi-objective approach for parameter estimation aiming at optimizing both the training loss and the computational load.
The conventional approach for parameter evaluation of non-linear forms of aforementioned isotherms involves linearization of the expressions through transformation, followed by the linear regression method.
In order to cope with these two difficulties, the aim of this article is to present a new approach for parameter estimation and modelling of batch cooling crystallizations.
Users spend a lot of time tuning algorithms for their specific problem domain, and this time could be saved by an automatic approach for parameter tuning.
Expectation Maximization (EM) is a popular approach for parameter estimation in many applications, such as image understanding, document classification, and genome data analysis.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com