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In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used.
All these approaches are data driven and focus on the construction and optimization of models that minimize the error between the observed and inferred mutation frequencies.
The model was selected assuming optimization of models, branches, and topology of the tree, and considering all criteria (−lnL, AIC, AICc, and BIC).
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But for traditional multiple kernel learning (MKL), many classification machines including INMKMHKS focus on MKL optimizations, for example, the optimization of model for a MKL.
Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters.
The GP has the capability to carry out simultaneous optimization of model relationship structures and parameters, as well as to identify the most important basis functions.
The problem of model establishment includes optimization of model parameters, kernel function selection, feature vector extraction, and unbalanced sample.
We consider the optimization of model parameters (including both dust model parameters and TCWV) through a least squares analysis.
The customization of the interfaced learners includes, for example, descriptor scaling, optimization of model hyper-parameters and appropriate stopping criteria.
The careful optimization of model parameters is necessary to strike a balance between simple and efficient computation and noise robustness.
In fact, ANN and ANFIS models need lots of input output data for optimization of model parameters which is not an easy task.
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