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The Electric Vehicle Charging Infrastructure Location Problem is an optimization problem that can be approached by linear programming, multi-objective optimization and genetic algorithms.
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Based on the fact that an arbitrary curve can be approached by a series of continuous but piecewise linear curves, the FGM is divided into several sub-layers and in each sub-layers the shear modulus is assumed to be linear function while the Poisson's ratio is assumed to be a constant.
The nonlinear system is approached by a sequence of linear time-varying systems, which allows many linear control techniques to be applied.
The strength of the association for either approach was determined by linear regression analysis using the program SPSS v17.0.
The difference between the proposed approach and the conventional Russell measure is that the proposed former approach for inefficiency identification can be solved by linear programming and the conventional latter, for efficiency identification, is solved by nonlinear programming.
In all cases, the gain matrices are determined by linear matrix inequality approach.
The sufficient conditions for the existence of filters and filter design methods are established by linear matrix inequality (LMI) approach, which can be solved efficiently by so called interior point algorithm.
Based on the result, the controller existence condition and robust H∞ state feedback controller design method are proposed by linear matrix inequality (LMI) approach without any decompositions of system matrices and equivalent transformation.
Eventually, you're bounded by linear growth.
T2 was determined by linear regression [47].
Trendlines were fitted by linear regression.
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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