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In this paper, we show that the internal stability of the resulting model, in closed loop with the same controller, is not always guaranteed if this controller is unstable and/or nonminimum phase, and that the classical closed-loop prediction-error identification methods present different properties regarding this stability issue.
Filter feature selection methods present different ranking algorithms; therefore, we propose an EMFFS method that combines the output of IG, gain ratio, chi-squared and ReliefF to find common features in the one-third split of the ranked features using NSL-KDD benchmark dataset in the Weka.
These methods present different properties and specific shortcomings [ 11].
The two methods present different costs and benefits, however.
Each biomarker and its associated detection methods present different particularities, drawbacks, and challenges.
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The proposed genetic fuzzy rule-based system is used to solve an electrical engineering problem and the results obtained are compared with other methods presenting different characteristics.
This method presented different results for the HotelExpedia and TripAdvisor datasets.
Therefore, materials prepared by different methods may present different band gaps.
Different methods will present different views of the phenomenon, but those disparities can be instructive.
All use different methods, present data from different sites, regions and years, and are not standardised to allow either direct comparison or meaningful combination in a single model.
Nonetheless, we consider that the three methods presented are different enough to allow a cross comparison, considering them as complementary.
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