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process optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
phase process » phase proteins (Expand Search), whole process (Expand Search), phase protein (Expand Search)
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Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
Published 2024“…Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”
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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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Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx
Published 2025“…</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …”
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Bayesian sequential design for sensitivity experiments with hybrid responses
Published 2023“…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …”
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DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
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Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
Published 2022“…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”
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Models and Dataset
Published 2025“…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …”
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Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
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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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Fortran & C++: design fractal-type optical diffractive element
Published 2022“…</p> <p>(2) calculate diffraction fields for fractal and/or grid-matrix (binary) phase-holograms.</p> <p>(3) optimize the fractal and/or grid-matrix holograms for given target diffraction images, using annealing algorithms. …”
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Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction
Published 2020“…We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.…”
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Seed mix selection model
Published 2022“…The genetic algorithm then operated over 1000 iterations, applying crossover and mutation processes to optimize bee richness. …”
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Flow diagram of the automatic animal detection and background reconstruction.
Published 2020“…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …”
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…Details on the data sourcing process, prompt engineering strategies for large language model (LLM)-based extraction, and validation protocols are provided in the Supplementary Information section.…”