Exact(9)
The model is run varying the learning parameter, momentum parameter, and number of cycles until RMSE is minimized.
A large number of inversions with various parameterizations of the Mars mantle were run, varying the number of layers and starting conductivity values.
In all 17 assays were run, varying the temperature (20, 37 and 55∘C), hydraulic retention time (2, 5 and 8 days) and N2-flow rates (5, 25 or 125 mL/min).
A total of 240 dynamic energy simulations were run varying these parameters, by using the EnergyPlus software with the Design Builder interface, which allowed the response variables to be determined for a set of sample buildings.
A sensitivity analysis was run varying, separately or in a combined way, the following parameters or operating conditions: ejector area ratio in a range of 33.1 86.6%; compressor frequency in the range of 30 60 Hz; ambient temperature in the range of −15 12 °C according to the standard UNI EN 14511/2011.
Once the agreement between analytical, numerical and experimental data is verified on a baseline undamaged condition, the parametric LISA model has been iteratively run, varying the position and the length of a crack on an aluminium skin panel, generating the virtual experience necessary to train a supervised learning regressor based on Artificial Neural Networks (ANNs).
Similar(50)
The SA had two steps: 1) a preliminary BACCO GEM-SA was conducted to identify a more accurate emulator sampling method and to screen out parameters with insignificant influence on model outcomes; and 2) final BACCO GEM-SA was conducted with optimal input design set for emulator training runs varying only the significant input parameters.
To achieve an optimal result, we performed a series of network inference runs varying the value of this parameter (0.001, 0.01 (0.005) 0.05) resulting in ten models (see Figure 2).
We performed a series of STRUCTURE runs varying between one and ten a-priori defined genetic subgroups or clusters (K = 1 to K = 10) using all 369 individuals and all 230 AFLP loci in order to detect the most optimal value of K in the total dataset.
For the next eight minutes, run at varying intervals, gradually increasing the time spent running at full speed.
STRUCTURE was run by varying the number of clusters (K) from 1 to 10; each K was run 3 times with a burn-in period of 100,000 and 100,000 MCMC (Markov Chain Monte Carlo) replications after burn-in.
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