Earlier experimental results are presented, with varying substrate and cladding combination; a subset of these results is analysed using single particle impact simulation, a more traditional approach in simulations of cold spray, and the smooth particle hydrodynamic (SPH) formulation to simulate multi-particle deposition.
Here, we provide a comprehensive evaluation of two data driven approaches to estimating waves near-shore (linear and ANN), and also contrast these with a more traditional spectral wave simulation model (SWAN).
Artificial neural networks (ANNs) can be used to predict energy consumption more reliably than traditional simulation models and regression techniques.
We compare the agent-based approach to more traditional hierarchical heuristics in an extensive simulation experiment.
The implementation of adaptive clinical trial methods, however, requires greater planning and simulation compared with a more traditional design, along with more advanced administrative infrastructure for trial execution.
In CLEIMS, learners experience an accurate, continuing simulation of a realistic clinical story from their likely future professional lives, interspersed with more traditional seminars and workshops on topics raised by the simulation.
The primary feature of the geostatistical approach, when compared to more traditional, interpolation-based approaches, is the use of simulations (i.e., CRs).
Verifying board designs in simulation offers distinct advantages over the more traditional prototyping approaches.
The SADP algorithm performs very well in all simulation scenarios and always better than more traditional controllers.
An additional simulation study confirmed the effectiveness of this model-based strategy over a more traditional simple random sampling strategy with respect to four regression model design criteria.
