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process optimization » model optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
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binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
process optimization » model optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
active swarm » active swarms (Expand Search), active state (Expand Search), active space (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025Subjects: -
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Proposed Algorithm.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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Comparisons between ADAM and NADAM optimizers.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
Published 2025“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
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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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Medium-scale dataset comparative analysis using the number of features selected.
Published 2023Subjects: -
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