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This allows ReaxFF to model complex processes involving multiple phases in contact with one another.
In particular, deep neural networks are applied in increasingly different fields to model complex processes.
Thus fractional order differential equations with p-Laplacian operator not only can describe the nonlinear phenomena in non-Newtonian fluids but also can model complex processes with long memory.
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It has been reported that AI-based inductive modeling techniques are frequently used to model complex process due to their powerful and non-linear model structures and their increased capabilities to capture the cause and effect relationship of such complex processes.
We describe empirical results from a multi-disciplinary project that support modeling complex processes of land-use and land-cover change in exurban parts of Southeastern Michigan.
For those unfamiliar with modelling complex processes, the operational Kt's are not necessarily the same as parameters assigned to the transporter.
In recent years soft computing methods are being increasingly used to model complex hydrologic processes.
A three-dimensional numerical solver is developed to model complex transport processes inside all components of a solid oxide fuel cell (SOFC).
Numerical results and numerical experimental correlation prove that the modelling technique and the methodologies applied to represent fibre bridging and frictional effects represent efficient tools to reliably model complex delamination processes.
Bayesian networks (BNs) are increasingly being used to model complex coastal processes due to their ability to integrate non-linear systems, their transparent probabilistic framework, and low computational cost.
The Nobel Prize for Chemistry went to Martin Karplus of Harvard University, Michael Levitt of Stanford University and Arieh Warshel of USC for their work using computers to model complex chemical processes.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com