Search alternatives:
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
major function » motor function (Expand Search), motor functions (Expand Search), major question (Expand Search)
binary major » binary mask (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)
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
major function » motor function (Expand Search), motor functions (Expand Search), major question (Expand Search)
binary major » binary mask (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)
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025Subjects: “…differential evolution algorithm…”
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QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm
Published 2020“…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …”
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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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Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods
Published 2022“…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …”
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