The model used a FEM simulation and a steepest decent method to find the best values for both variables.
In the isotropic case, the equation u t = div ( ∂ ξ f ( D u ) ) becomes u t = div ( D u | D u | ) when the Lagrangian f : R N → [ 0, + ∞ ] is given by f = ∥ ξ ∥, where ∥ ξ ∥ is the usual l 2 -norm; i.e., ∥ ξ ∥ : = ( ∑ i = 1 N ξ i 2 ) 1 2. Let us recall that this PDE appears when one uses the steepest decent method to minimize the total variation.
However, even though the sure independence screening seems to be a decent method indeed, and we have contented ourselves with using it for the marker preselection for the time being, there probably is room for improvement in this respect.
Then, in order to enhance the adaptability and real-time performance of proposed IDMs, two online optimization algorithms, including exact online programming driving (EOPD) and inexact online programming driving (IOPD), are developed by improved gradient descent and stochastic meta-decent method to update the controller's output online.
This prepared system was then subjected to energy minimization up to a maximum of 3000 steps using a steepest decent method or until a gradient threshold (25 kcal/mol/Å) was not reached.
Using a steepest decent method, the heat load on the mirrors is successfully reduced to the acceptable level by flattening the RF power profile on the mirrors keeping the scattering of the RF power to a minimum from the mirrors.
The parameters for running both methods were set similar to [ 20], that is, with QUASI-P a gradient decent method was used for optimization (start step size 0.01, stopping condition epsilon 0.01).
Based on this mathematical model, the steepest decent method is used to search for the optimal process parameters.
The accuracies on Datasets 4 and 5 are 82.75% and 80.42%, respectively, which shows DCN-based method has a decent sensitivity to distinguish and classify closely-related species, i.e. in the deeper level of the phylogenetic tree, as dataset 4 contains only genomes from Bacterial Division 12, and dataset 5 contains both Division 12 and 13.
When the solution is close to the correct one, the Gauss Newton method is applied to the training because it is more accurate and faster near an error minimum than the gradient decent method.
