يعرض 81 - 100 نتائج من 149 نتيجة بحث عن '(( binary based models optimization algorithm ) OR ( binary data global optimization algorithm ))', وقت الاستعلام: 0.45s تنقيح النتائج
  1. 81

    Results of KNN. حسب Balraj Preet Kaur (20370832)

    منشور في 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. 82

    After upsampling. حسب Balraj Preet Kaur (20370832)

    منشور في 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. 83

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

    منشور في 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. 84

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

    منشور في 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. …"
  5. 85

    <i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

    منشور في 2023
    "…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i><sub><i>δ</i></sub>) based on this metric. <b>(E)</b> Starting from the interaction at the top of <i>I</i><sub><i>δ</i></sub>, <i>hi</i>PRS constructs <i>I</i><sub><i>K</i></sub>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …"
  6. 86

    Flowchart scheme of the ML-based model. حسب Noshaba Qasmi (20405009)

    منشور في 2024
    "…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …"
  7. 87

    A* Path-Finding Algorithm to Determine Cell Connections حسب Max Weng (22327159)

    منشور في 2025
    "…Future work aims to generalize this algorithm for broader biological applications by training additional Cellpose models and adapting the A* framework.…"
  8. 88

    SHAP bar plot. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  9. 89

    Display of the web prediction interface. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  10. 90

    Sample screening flowchart. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  11. 91

    Descriptive statistics for variables. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  12. 92

    SHAP summary plot. حسب Meng Cao (105914)

    منشور في 2025
    الموضوعات:
  13. 93

    Plan frame of the house. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
  14. 94

    Ablation test results. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
  15. 95

    Hyperparameter selection test. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
  16. 96

    Multiple index test results of different methods. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
  17. 97

    Backtracking strategy diagram. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
  18. 98

    Comparison of differences in literature methods. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
  19. 99

    Schematic of iteration process of IDE-IIGA. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
  20. 100

    Schematic diagram of IGA chromosome coding. حسب Ling Zhao (111365)

    منشور في 2025
    "…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"