يعرض 21 - 40 نتائج من 47 نتيجة بحث عن '(( binary tasks based optimization algorithm ) OR ( single layer wolf optimization algorithm ))', وقت الاستعلام: 0.55s تنقيح النتائج
  1. 21

    Description of the datasets. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  2. 22

    S and V shaped transfer functions. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  3. 23

    S- and V-Type transfer function diagrams. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  4. 24

    Collaborative hunting behavior. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  5. 25

    Friedman average rank sum test results. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  6. 26

    IRBMO vs. variant comparison adaptation data. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
  7. 27

    . Fitness curve. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  8. 28

    Partial faults features. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  9. 29

    Diagram of faults identification. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  10. 30

    Confusion matrix. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  11. 31

    Sample group. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  12. 32

    Data in the experiment. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  13. 33

    Diagram of attention mechanism. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  14. 34

    Accuracy curve. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  15. 35

    Structure of MLP. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  16. 36

    Fault recording signal. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  17. 37

    Ablation study. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  18. 38

    Dual-channel MLP-Attention model. حسب Ning Ji (325849)

    منشور في 2024
    "…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …"
  19. 39
  20. 40

    Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP حسب Xiaoyuan Wang (492534)

    منشور في 2022
    "…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …"