Cellular Automata (CA) have been introduced many decades ago as one of the most efficient parallel computational models able to simulate various physical processes and systems where the interactions are local.
Moreover, it explores a range of scenarios, with the objective to determine the best meteorologic conditions for soil property retrieval and hence the most efficient use of computational resources when applying the methodology at large scales.
However, the fourth-order accurate implicit Runge Kutta scheme is found to be the most efficient in terms of computational cost for a given accuracy level as compared to the lower-order schemes, in spite of the added cost per time step, and the benefits of this scheme increase for tighter error tolerances.
The most efficient way, from a computational point of view, to predict the temperature evolution in time and space of a ground volume in contact with a system of BHE, is the recursive calculation of a basic thermal response factor, evaluated at different time steps and for given different heat pulses representing the building energy demand.
From the computational viewpoint, the most efficient approaches are the pole-residue expansion based on eigenfunction projection, and the low-order Padé approximation.
Uniform grid density distribution is found to be the most efficient choice in terms of balance between computational cost and numerical accuracy.
This approach does not account for the redundancies that are necessarily involved and, therefore, it is not the most efficient from the points of view of computational cost and time needed to generate the database.
Through this manner, the most efficient DE variant is expected to obtain the most computational resources during the optimization process.
Using microarray technology combined with computational analysis is one of the most efficient and cost-effective methods for studying cancer.
For a restricted set of parameters we provide analytical results; we also design a very efficient computational method to calculate the mean, which works for most of the parameter values, and any colony size, no matter how large.
