Search alternatives:
process optimization » model optimization (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
ramp process » jump process (Expand Search), acp process (Expand Search), creep process (Expand Search)
process optimization » model optimization (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
ramp process » jump process (Expand Search), acp process (Expand Search), creep process (Expand Search)
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Descriptive analysis of the outcomes by the optimized LSTM using several optimization algorithms.
Published 2025Subjects: -
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Performance of the bAD-PSO-Guided WOA algorithm compared with another algorithm.
Published 2025Subjects: -
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Performance of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm.
Published 2025Subjects: -
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Analysis plots of the obtained results using the proposed AD-PSO-Guided WOA LSTM algorithm.
Published 2025Subjects: -
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The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. meta-heuristic algorithms boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. feature selection algorithm boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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Pseudo Code of RBMO.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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P-value on CEC-2017(Dim = 30).
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”