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In this paper, an efficient yet easy to implement method is proposed to parameterise the equivalent circuit model of batteries utilising the advances of evolutionary algorithms (EAs).
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Moreover, the implemented method is highly parallel and therefore suitable for High Performance Computing.
The first implemented method is a numerical-multiphysics method which couples computational fluid dynamics and heat-transfer equations.
The experimental validation of the implemented method showed that the implemented method is able to assess quantitatively the linearity of the system.
The most widely implemented method is patterning the graphene into a narrow ribbon called graphene nanoribbon (GNR) [4].
The principle of the implemented method is to refine an initial solution of the local tomography problem, knowing that middle and high-frequency features are usually well recovered.
Therefore, the implemented method is suitable for real-time posture estimation without using high-performance hardware.
However, we observed, as also noted by Hu [ 38] in their own model, that the implemented method is sensitive to outliers.
The implemented method was tested comparing the wind map with both literature and the available experimental data.
His implemented method was a fuzzy regression nearest neighbor ANN model.
The implemented method was evaluated for different levels of η-shrinkage.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com