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This work demonstrates that the multiple model methodology can be recast into a Supervisory approach, whereby the supervisor is employed as a selector.
The multiple model methodology may be useful here as well.
The multiple model methodology allows us to obtain a handle on process complexity on one hand and combine it with effective tools of analysis on the other.
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The different insights brought by different models also make the multiple-model methodology and hybrid modelling approaches desired choices for modelling and understanding the mRNA translation process.
Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise.
Interacting multiple model.
Multiple occurrences of a shorter constituent oligonucleotide might lead to an oligomer being apparently overrepresented, respective to a random counterpart, due to the zero-order Markov model methodology.
The proposed methodology utilizes multiple models of the robot for its identification in an adaptive and learning control framework.
This data-driven methodology employs multiple models, one for each decision point, to capture the time-varying relationships.
In this study, adaptive control methodology using multiple models is proposed to design a reconfigurable controller for nonlinear systems.
Ptolemy II advocates a component-based design methodology, and hierarchically integrates multiple models of computation, which can be used to capture different design perspectives.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com