Showing 21 - 40 results of 105 for search '(( binary model which optimization algorithm ) OR ( binary edge wolf optimization algorithm ))', query time: 0.40s Refine Results
  1. 21

    Best optimizer results of Extra tree. by Balraj Preet Kaur (20370832)

    Published 2024
    “…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. 22

    Best optimizer results of Random Forest. by Balraj Preet Kaur (20370832)

    Published 2024
    “…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. 23

    Best optimizer result for Extra tree. by Balraj Preet Kaur (20370832)

    Published 2024
    “…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. …”
  4. 24

    The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
  5. 25

    QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm by Z.Y. Algamal (5547620)

    Published 2020
    “…The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …”
  6. 26
  7. 27

    Statistical summary of all models. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  8. 28

    Classification performance of ML and DL models. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  9. 29
  10. 30

    IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
  11. 31

    IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
  12. 32

    ROC curve for binary classification. by Nicodemus Songose Awarayi (18414494)

    Published 2024
    “…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”
  13. 33

    Confusion matrix for binary classification. by Nicodemus Songose Awarayi (18414494)

    Published 2024
    “…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”
  14. 34

    Classification performance after optimization. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  15. 35

    ANOVA test for optimization results. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  16. 36

    Wilcoxon test results for optimization. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  17. 37

    Results of KNN. by Balraj Preet Kaur (20370832)

    Published 2024
    “…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. …”
  18. 38

    Comparison of key techniques in their literature. by Balraj Preet Kaur (20370832)

    Published 2024
    “…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. …”
  19. 39

    SHAP analysis mean value. by Balraj Preet Kaur (20370832)

    Published 2024
    “…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. …”
  20. 40

    Proposed methodology. by Balraj Preet Kaur (20370832)

    Published 2024
    “…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. …”