بدائل البحث:
design optimization » bayesian optimization (توسيع البحث)
models optimization » model optimization (توسيع البحث), process optimization (توسيع البحث), wolf optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based models » based model (توسيع البحث)
binary ii » binary _ (توسيع البحث), binary b (توسيع البحث)
ii design » i design (توسيع البحث), _ design (توسيع البحث), co design (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
models optimization » model optimization (توسيع البحث), process optimization (توسيع البحث), wolf optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based models » based model (توسيع البحث)
binary ii » binary _ (توسيع البحث), binary b (توسيع البحث)
ii design » i design (توسيع البحث), _ design (توسيع البحث), co design (توسيع البحث)
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143
Seed mix selection model
منشور في 2022"…</p> <p> </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …"
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144
Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level
منشور في 2021"…Propensity score matching is a popular method to infer causal relationships in observational studies with two treatment arms. Few studies, however, have used matching designs with more than two groups, due to the complexity of matching algorithms. …"
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145
Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model
منشور في 2019"…Because of the semipredictive nature of the symmetric eNRTL-SAC model, the segment parameter regression is a critical step for solubility prediction accuracy. A particle swarm optimization algorithm is incorporated to preregress conceptual segment parameters of solutes. …"
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146
Testing results for classifying AD, MCI and NC.
منشور في 2024"…The model further showed superior results on binary classification compared with existing methods. …"
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147
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148
Quadratic polynomial in 2D image plane.
منشور في 2024"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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149
Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease
منشور في 2025"…</p> <p>Psoas computerized tomography radiomics-based ML models effectively predict the response of patients with CD to IFX therapy, with the eXtreme Gradient Boosting model exhibiting superior performance.…"
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150
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151
Fortran & C++: design fractal-type optical diffractive element
منشور في 2022"…</p> <p>(3) optimize the fractal and/or grid-matrix holograms for given target diffraction images, using annealing algorithms. …"
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152
DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
منشور في 2021"…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …"
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153
Models and Dataset
منشور في 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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154
Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data
منشور في 2021"…In contrast to most existing approaches which are designed to maximize the expected survival time under a binary treatment framework, the proposed method solves the multicategory treatment problem given multiple stages for censored data. …"
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155
MCLP_quantum_annealer_V0.5
منشور في 2025"…Finally, for spatial relationship verification, a Spatial Coverage Consistency Checking Operator for MCLP Results (SCCCOMR) is designed. Theoretical and applied experiments are conducted using four solvers: QBSolv, D-Wave Hybrid binary quadratic model 2, D-Wave Advantage system 4.1, and Gurobi. …"
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156
Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX
منشور في 2021"…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …"
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157
Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx
منشور في 2025"…In addition, YOLOv8-FPDW was more competitive than mainstream object detection algorithms. The study predicted the optimal harvest period for litchis, providing scientific support for orchard batch harvesting and fine management.…"
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158
Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf
منشور في 2019"…<p>The Fujitsu Digital Annealer is designed to solve fully connected quadratic unconstrained binary optimization (QUBO) problems. …"
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159
Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
منشور في 2024"…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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160
Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish)
منشور في 2024"…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …"