Search alternatives:
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data swarm » data share (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data swarm » data share (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.
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Performance of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm.
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Analysis plots of the obtained results using the proposed AD-PSO-Guided WOA LSTM algorithm.
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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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Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model
Published 2019“…Because of the semipredictive nature of the symmetric eNRTL-SAC model, the segment parameter regression is a critical step for solubility prediction accuracy. A particle swarm optimization algorithm is incorporated to preregress conceptual segment parameters of solutes. …”
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