Search alternatives:
resource optimization » resource utilization (Expand Search), resource limitations (Expand Search)
driven optimization » design optimization (Expand Search), process optimization (Expand Search)
also resource » actor resource (Expand Search), value resource (Expand Search), low resource (Expand Search)
binary wave » binary image (Expand Search)
resource optimization » resource utilization (Expand Search), resource limitations (Expand Search)
driven optimization » design optimization (Expand Search), process optimization (Expand Search)
also resource » actor resource (Expand Search), value resource (Expand Search), low resource (Expand Search)
binary wave » binary image (Expand Search)
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1
Dynamic resource allocation process.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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2
Supplementary file 1_Encodings of the weighted MAX k-CUT problem on qubit systems.pdf
Published 2025“…This study explores encoding methods for MAX k-CUT on qubit systems by utilizing quantum approximate optimization algorithms (QAOA) and addressing the challenge of encoding integer values on quantum devices with binary variables. …”
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3
Confusion matrix.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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4
Parameter settings.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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5
Event-driven data flow processing.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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6
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”