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To verify the effectiveness of the proposed GSA based filter modeling, different sets of initial population with the presence of different measurable noises are given and tested in simulations.
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Additionally, the application of the profile aimed primarily at demonstrating its use to model different sets of biomedical entity classes and their relationships.
In order to collect the data necessary to run the model, different sets of questionnaires were prepared for all relevant stakeholders.
Each of the analyses was done by different investigators, using different models, different sets of assumptions, and different populations.
Some variations in results between these two analyses probably stem from their use of different models, different sets of data, and different objectives and hypotheses.
One unique feature of our model is based on the observation that the similarity between some sequences is determined more accurately with one type of similarity measure rather than another, hence in our model, different sets of weights can be associated with different sequences (i.e. sequences to be classified).
The initial model is then updated to reference models using different sets of ambient vibration measurements at the reference state of the building.
As the zero and the truncated Poisson parts of the model gave different sets of significant variables, this further suggested the need for this type of model.
Significant changes in model fit were calculated by the F-ratio of the change in R between models with different sets of predictors.
A two-dimensional model with different sets of boundary conditions has been developed for limiting current conditions.
In particular, predictions using the enhanced creep model with different sets of thermal creep parameters were compared with results of the thermal relaxation test conducted by MacLean, indicating different thermal creep resistance.
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