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We developed a population PK model using nonlinear mixed effect modeling (NONMEM) with the NONMEM algorithm.
The soil-pile interaction was modeled with a distributed spring model using nonlinear API p-y curves.
A population PK model using nonlinear mixed-effect modeling (NONMEM) was developed.
In our previous work, we developed a consensus model using nonlinear Support Vector Machine (SVM), Associative Neural Networks (ASNN), and Random Forest (RF) approaches.
All data were obtained in triplicate and analyzed by curve fitting to a one-site binding model using nonlinear regression employing Graphpad Prism software (version 4.0) to determine K d and B max values.
To determine the kinetic parameters kcat and KM, all data were fit to a Michaelis Menten model, using nonlinear regression.
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The specimens are modeled using nonlinear finite element method and analyzed under cyclic loading.
The results are compared with those obtained by traditional mechanistic modeling using nonlinear parameter estimation.
The beams, columns, braces and zipper columns are modeled using nonlinear force-formulation frame elements and nonlinear geometric effects are included by utilizing corotational transformation.
The yarns' uniaxial tensile response is modeled using nonlinear springs within the unit cell formulation while a nonlinear rotational spring is used to define the fabric's shear stiffness.
Next, both the ship structure and the tubular braces/legs are modeled using nonlinear shell finite elements, and the effect of ship-platform interaction on the damage distribution is investigated.
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model using several
model using standard
model using stochastic
model using different
model using probabilistic
model using frequency-domain
model using individual
model using multiple
model using negative
model using multi-body
model using preferred
model assuming nonlinear
model using maximum
model using regional
model using complementary
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