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By virtue of mechanism method and TS fuzzy modeling technique, a partial linear structured mechanism model is firstly obtained, which contains a parametric linear part with unknown coefficients and a non-parametric part with unknown functional expression.
A more accurate kinetic model is firstly established.
The surrogate model is firstly constructed by basic sparse samples.
The mathematical basis of this model is firstly presented.
A cast model is firstly created from a patient's image to develop patient-specific features.
The newly presented model is firstly validated with a commercial simulator and some core flooding experiments.
The model is firstly validated by comparison with the experimental data from an in-service GHE.
A quantifiable evaluation model is firstly derived to evaluate different kinds of strategies.
In order to mitigate vulnerability of UTN system, a robust bi-level model is firstly presented.
The T S fuzzy model is firstly applied to represent the nonlinear electromagnetic suspension systems.
The present model is firstly validated using several available laboratory experiments.
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