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Agent-based modeling (ABM) is the second and more recent modeling approach in the computational and simulation.
This approach is a rules-based modeling approach in which each component of the model system is represented by an agent with a certain behavior based on its biological functions.
This example of hybrid ABM‐PK/PD model highlights the ability of ABM to integrate different modeling techniques, overcoming the respective limitations associated with using either modeling approach in isolation.
CMAP is a coarse-grained graphical modeling approach in which the system of interest is modeled as an interaction map between functional elements of the system, in a manner similar to portrayals of signaling pathways commonly used by molecular cell biologists.
To this end we use a detailed modeling approach in which we combine an intra-cellular model of viral growth and the RNA silencing pathway with inter-cellular tissue dynamics.
The present model is shown to yield significant improvement over a homogeneous modeling approach in predicting chemical species mole fractions, as well as accurate predictions of temperature and pressure.
Model validation against experimental data demonstrates the capabilities of the modeling approach in predicting the refrigerant mass migration among the components during shut-down, and the resulting refrigerant redistribution behaviors during start-up.
Cubist is an implementation of tree based modeling approach in R where a resulting tree is a set of linear models at each node starting from the root to the last node.
The modeling approach in Matlab/Simulink makes controller design and simulation verification effective.
The collected data were analyzed using factor analysis and structural equation modeling approach in hope to make significant inferences.
This discrepancy is due to limitations of the modeling approach in accounting for plastic response to tangential loading.
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