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Repeatability studies were performed on the optimum parameter conditions.
Our analysis shows that with optimum parameter settings, the LTE Rel.
The convergence rate of the conventional iterative method is low even for the optimum parameter.
We use only image features as input for modified BOW with the optimum parameter settings.
After the GMM optimum parameter determination, each atomic column thickness was assigned to a Gaussian distribution.
The selection of the optimum parameter value for these classifiers is described below.
The optimum parameter space for this design has been explored, and factors controlling performance are identified.
The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated.
Optimum parameter combinations that minimize the transient time are also identified from the studies.
The optimum parameter set for genetic algorithm is obtained by Taguchi experimental design.
The mean ensemble is found to be efficient than single best simulation with optimum parameter combinations.
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