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The dispersion of the particles due to turbulence is predicted using a stochastic tracking model, in conjunction with the k ε equations for the gas phase.
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By using a stochastic analysis method, the probability constrained tracking control problem is solved and sufficient conditions are obtained in terms of recursive linear matrix inequalities.
This contribution implements the CA that was proposed by Isard and Blake [24, 25] to track active contours using a stochastic approach.
Using a stochastic model of storm motion derived from historic tracks, this paper explores the relationship between lead time and track uncertainty for Atlantic hurricanes and the implications of this relationship for evacuation decisions.
Uncertainty is considered using a stochastic ToBloOM.
We modify their simulation model to analyse our hypothesis using a stochastic model.
This implies using a stochastic imputation.
The Random Ray Method (TRRM) uses a stochastic rather than deterministic discretization of characteristic tracks to integrate the phase space of a problem.
Therefore, in addition, we use a stochastic inversion technique.
The developed weight adaptive laws use a stochastic approximation algorithm.
The UPE project has used a stochastic approach instead.
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