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The proposed approach is modeled using Discrete-Time-Markov Chain (Discrete-Time-Markov Chainn wireless mesh networks.
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Using the present approach, each blade row is modeled using a computational grid spanning a single blade passage regardless of the the actual blade counts.
The soil behind the abutments and under the approach slabs was modeled using Spring1 elements, which connect from the defined node to the ground.
Time trends in IR were modelled using several approaches.
Therefore, alternative approach is to model process using limited experimental points representing all variable space.
Finally, the approach is tested using the Common Aero Vehicle-H model.
A probabilistic approach is used to model the adversarial environment.
Markovian approach is used to model the system behavior.
Then, this approach is used to model cognitive uncertainties of parameters.
In [32], this approach is used to model the MC network as a biological circuit.
In the present study, the Lagrangian approach is used for modeling the fluid and sediment domain.
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