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The solution was updated twice in three days.
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Since there are no overlapping loops, the solution is updated.
For PSO, the local and global best solution are updated in this step.
The clustering solution is updated by a reclustering algorithm after adding every new site.
When the solution is updated, the resulting solution from the previous stage will be used as the initial guess for the next iteration.
As illustrated in Fig. 1, during the process of DRL, the solution is updated according to its performance as evaluated by the corresponding reward signal.
The small time steps maintain numerical stability, while the overall solution is updated on a larger time step to reduce computational cost.
The SQP implementation consists of two loops: the phase solution is updated at each fiiteration in major loop with k as the counter, while itself contains an inner QP loop to solve for optimum search direction d k.
During the course of folding, the optimal solution is updated as the dynamic contact map changes from its initial given state to the final native state.
The new solution is updated as x t = x t- 1 + α p t.
These transformations of NM worked if there is no improvement in the fitness function value after the solution is updating using the original LLP.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com