Search alternatives:
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
phase optimization » whale optimization (Expand Search), based optimization (Expand Search), path optimization (Expand Search)
image function » immune function (Expand Search), image fusion (Expand Search), rate function (Expand Search)
primary data » primary care (Expand Search)
data phase » late phase (Expand Search)
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
phase optimization » whale optimization (Expand Search), based optimization (Expand Search), path optimization (Expand Search)
image function » immune function (Expand Search), image fusion (Expand Search), rate function (Expand Search)
primary data » primary care (Expand Search)
data phase » late phase (Expand Search)
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Iteration curve of the optimization process.
Published 2025“…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …”
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Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning
Published 2021“…Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. In addition, we compared four common machine learning algorithms, including naive Bayes, decision tree, K-nearest neighbors, support vector machine (SVM), and fully connected network. …”
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Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning
Published 2021“…Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. In addition, we compared four common machine learning algorithms, including naive Bayes, decision tree, K-nearest neighbors, support vector machine (SVM), and fully connected network. …”
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Data Sheet 1_TBESO-BP: an improved regression model for predicting subclinical mastitis.pdf
Published 2025“…The model is based on TBESO (Multi-strategy Boosted Snake Optimizer) and utilizes monthly Dairy Herd Improvement (DHI) data to forecast the status of subclinical mastitis in cows.…”