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The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics.
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Various simulation approaches have been employed.
Multi-agent-based simulation approaches have been noted as the potential solution for this [67] by considering agent-based simulations.
In the last decades, with the advances in computational resources, numerical simulation approaches have become increasingly popular.
Molecular simulation approaches have been used to enhance the understanding of complex chemical interactions in coatings related processes.
In addition, using simulation approaches have not been sufficient for developed complex cloud services that omit some critical test cases in the state space of the model.
The simulation approaches have provided important insights into the dynamics of compressible homogeneous flows and now, inhomogeneous flows, and the averaged approaches have traditionally been the methodology used in replicating and predicting the more complex engineering flows.
Both experimental and simulation approaches have shown that artificial selection for production traits influences the performance-resistance relationship [27], [28], but the outcomes are often contradictory and the underlying mechanisms not fully understood (as reviewed by [27]).
Modeling and simulation approaches have become an integral part of drug discovery and development.
Molecular dynamics simulation approaches have also been extensively used to report the structural consequences of the deleterious predicted point mutations.
In addition to the results obtained from kinetic and structural studies, molecular dynamics simulation approaches have further enhanced our understanding of conformational dynamics of the polymerase-catalyzed nucleotidyl transfer reaction that results in base selectivity.
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