Showing 61 - 80 results of 142 for search '(( final while process optimization algorithm ) OR ( binary step process optimization algorithm ))', query time: 1.58s Refine Results
  1. 61

    Time taken to simulate running 30 switch cycles. by Jianhua He (341366)

    Published 2024
    “…The wavelet reconstruction algorithm can simulate all kinds of fast changes in the actual working process more accurately and compress irrelevant information while retaining key signal features, so as to optimize the simulation performance of the model. …”
  2. 62

    DataSheet1_A mechanobiological computer optimization framework to design scaffolds to enhance bone regeneration.docx by Camille Perier-Metz (9625289)

    Published 2022
    “…Therefore, we propose a computer framework to optimize scaffold designs that allows to promote the final bone regeneration outcome. …”
  3. 63

    Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) by Daniel Pérez Palau (11097348)

    Published 2024
    “…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”
  4. 64

    Specific architecture of modern ICS. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  5. 65

    Comparison of accuracy of feature classification. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  6. 66

    Pseudo-code for the study design model. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  7. 67

    CNN-GRU based on GA. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  8. 68

    CICIDS2017 Training results on the dataset. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  9. 69

    1d-MC model architecture. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  10. 70

    The experimental basic environment parameters. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  11. 71

    GA pseudo-code. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  12. 72

    1d-MS CNN + GRU model structure. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  13. 73

    Comparison of running times of four models. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  14. 74

    CNN-GRU model. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  15. 75

    Comparison of intrusion detection results. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  16. 76

    ICN pooling layer operation. by Jianpeng Zhang (528185)

    Published 2025
    “…Genetic algorithm is utilized to solve and optimize the data, one-dimensional multi-scale convolutional neural network is combined with gated recurrent unit to improve the network intrusion detection model, and finally the detection and defense of industrial control network intrusion is completed. …”
  17. 77
  18. 78

    Table 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

    Published 2025
    “…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
  19. 79

    Table 4_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

    Published 2025
    “…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
  20. 80

    Table 5_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

    Published 2025
    “…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”