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common optimization » codon optimization (Expand Search), carbon optimization (Expand Search), cosmic optimization (Expand Search)
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based wolf » based whole (Expand Search), based work (Expand Search), based well (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
a common » _ common (Expand Search)
common optimization » codon optimization (Expand Search), carbon optimization (Expand Search), cosmic optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
based wolf » based whole (Expand Search), based work (Expand Search), based well (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
a common » _ common (Expand Search)
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025“…A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
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Performance on GradEva.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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The considered test problems.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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Performance on FunEva.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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Performance on Iter.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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Continuation of Table 2.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf
Published 2022“…Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training.…”
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MCLP_quantum_annealer_V0.5
Published 2025“…Currently, classical high-performance and parallel spatial computing architectures are commonly employed to solve geospatial optimization problems. …”
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Generalized Tensor Decomposition With Features on Multiple Modes
Published 2021“…Our proposal handles a broad range of data types, including continuous, count, and binary observations. …”
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Contextual Dynamic Pricing with Strategic Buyers
Published 2024“…This underscores the rate optimality of our policy. Importantly, our policy is not a mere amalgamation of existing dynamic pricing policies and strategic behavior handling algorithms. …”
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Bayesian sequential design for sensitivity experiments with hybrid responses
Published 2023“…<p>In experimental design, a common problem seen in practice is when the result includes one binary response and multiple continuous responses. …”
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
Published 2020“…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”
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Table_1_Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.DOCX
Published 2022“…Decision trees were constructed by a hierarchical binary recursive partitioning algorithm to predict the BP-lowering of 10–30% off the maximal value when antihypertensive treatment was given in patients with an extremely high BP (above 220/110 or 180/105 mmHg for patients receiving thrombolysis), according to the American Heart Association/American Stroke Association (AHA/ASA), the European Society of Cardiology, and the European Society of Hypertension (ESC/ESH) guidelines. …”
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Supplementary Material 8
Published 2025“…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…”
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