يعرض 61 - 79 نتائج من 79 نتيجة بحث عن '(( binary data global optimization algorithm ) OR ( binary a wolf optimization algorithm ))', وقت الاستعلام: 0.42s تنقيح النتائج
  1. 61

    After upsampling. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  2. 62

    Results of Extra tree. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
  3. 63

    Gradient boosting classifier results. حسب Balraj Preet Kaur (20370832)

    منشور في 2024
    "…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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    Summary of literature review. حسب Muhammad Ayyaz Sheikh (18610943)

    منشور في 2024
    "…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
  7. 67

    Topic description. حسب Muhammad Ayyaz Sheikh (18610943)

    منشور في 2024
    "…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
  8. 68

    Notations along with their descriptions. حسب Muhammad Ayyaz Sheikh (18610943)

    منشور في 2024
    "…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
  9. 69

    Detail of the topics extracted from DUC2002. حسب Muhammad Ayyaz Sheikh (18610943)

    منشور في 2024
    "…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
  10. 70

    DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf حسب Marcel Dahms (9160118)

    منشور في 2022
    "…Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training.…"
  11. 71

    Generalized Tensor Decomposition With Features on Multiple Modes حسب Jiaxin Hu (1327875)

    منشور في 2021
    "…Our proposal handles a broad range of data types, including continuous, count, and binary observations. …"
  12. 72

    Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

    منشور في 2024
    "…In this direction, the option of estimating the statistics of the model directly from the training image (performing a refined pattern search instead of simulating data) is a very promising.<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…"
  13. 73

    Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model حسب Getachew S. Molla (6416744)

    منشور في 2019
    "…The methodology incorporates key features of the symmetric eNRTL-SAC model structure to reduce the number of parameters and uses a hybrid of global search algorithms for parameter estimation. …"
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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
    "…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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    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. …"
  18. 78

    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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