يعرض 1 - 20 نتائج من 159 نتيجة بحث عن '(( binary task derived optimization algorithm ) OR ( primary data robust optimization algorithm ))', وقت الاستعلام: 0.35s تنقيح النتائج
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5

    Pseudocode of artificial dragonfly algorithm. حسب Ghassan Ahmed Ali (17041488)

    منشور في 2023
    "…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
  6. 6

    The Hopfield artificial neural network algorithm. حسب Ghassan Ahmed Ali (17041488)

    منشور في 2023
    "…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
  7. 7

    Robustness Analysis of each model. حسب Hao Yang (328526)

    منشور في 2025
    "…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
  8. 8
  9. 9
  10. 10

    Flow diagram of Wan Abdullah method for HNN. حسب Ghassan Ahmed Ali (17041488)

    منشور في 2023
    "…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
  11. 11

    Training error and accuracy for all HNN models. حسب Ghassan Ahmed Ali (17041488)

    منشور في 2023
    "…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
  12. 12

    G<i>m</i>R performance of various HNN-EB<i>k</i>SAT models. حسب Ghassan Ahmed Ali (17041488)

    منشور في 2023
    "…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
  13. 13

    <i>MAPE performance of various</i> HNN-EB<i>k</i>SAT models. حسب Ghassan Ahmed Ali (17041488)

    منشور في 2023
    "…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
  14. 14

    RMSE performance of various HNN-EB<i>k</i>SAT models. حسب Ghassan Ahmed Ali (17041488)

    منشور في 2023
    "…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
  15. 15

    MLP vs classification algorithms. حسب Mohd Mustaqeem (19106494)

    منشور في 2024
    "…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
  16. 16

    S1 Data - حسب Guangwei Liu (181992)

    منشور في 2023
    "…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"
  17. 17

    Curve of step response signal of 6 algorithms. حسب Guangwei Liu (181992)

    منشور في 2023
    "…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"
  18. 18
  19. 19

    Wilcoxon’s rank sum test results. حسب Guangwei Liu (181992)

    منشور في 2023
    "…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"
  20. 20

    Flowchart of MSHHOTSA. حسب Guangwei Liu (181992)

    منشور في 2023
    "…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"