يعرض 141 - 160 نتائج من 171 نتيجة بحث عن '(( binary task derived optimization algorithm ) OR ( binary data based optimization algorithm ))*', وقت الاستعلام: 0.47s تنقيح النتائج
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    GSE96058 information. حسب Sepideh Zununi Vahed (9861298)

    منشور في 2024
    "…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"
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    The performance of classifiers. حسب Sepideh Zununi Vahed (9861298)

    منشور في 2024
    "…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"
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    Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf حسب Muhammad Awais (263096)

    منشور في 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 حسب Pangpang Liu (18886419)

    منشور في 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 حسب Veera Narayana Balabathina (22518524)

    منشور في 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). …"