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Showing 1 - 20 results of 169 for search '(( less based process simulation algorithm ) OR ( binary image all optimization algorithm ))', query time: 0.55s Refine Results
  1. 1
    RL learning process.

    RL learning process. by Sardor Israilov (14609720)

    Published 2023
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  2. 2
    Procedure of the DCT-based EIT algorithm.

    Procedure of the DCT-based EIT algorithm. by Rongqing Chen (249906)

    Published 2023
    “…In this contribution, we introduce a discrete cosine transformation-based (DCT-based) EIT reconstruction algorithm to demonstrate a way to incorporate the structural prior with the EIT reconstruction process. …”
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  3. 3
    Influence of the applied voltage on the learning process.

    Influence of the applied voltage on the learning process. by Sardor Israilov (14609720)

    Published 2023
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  4. 4
    The learning process and the quality of the control for the pendulum.

    The learning process and the quality of the control for the pendulum. by Sardor Israilov (14609720)

    Published 2023
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  5. 5
    Transient response of different algorithms-based 2-DOF PIDA controllers.

    Transient response of different algorithms-based 2-DOF PIDA controllers. by Erdal Eker (19251018)

    Published 2025
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  6. 6
    Configuration of simulation parameters.

    Configuration of simulation parameters. by Shehr Bano (20421706)

    Published 2024
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  7. 7
    Steady-state response of different algorithms based 2-DOF PIDA controllers.

    Steady-state response of different algorithms based 2-DOF PIDA controllers. by Erdal Eker (19251018)

    Published 2025
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  8. 8
    Filtering process diagram.

    Filtering process diagram. by Celia Tendero Delicado (20495955)

    Published 2025
    “…The testing volumes come from the Mayo clinic database and consist of CT volumes at full and at simulated low dose. The GPU parallelizations reach speedups of over 2700 and take less than 0.1 seconds to filter more than 300 slices. …”
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  9. 9
    Time domain performance metrics of different algorithms based 2-DOF PIDA controllers.

    Time domain performance metrics of different algorithms based 2-DOF PIDA controllers. by Erdal Eker (19251018)

    Published 2025
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  10. 10
    Best convergence curves of the algorithms with respect to iteration number.

    Best convergence curves of the algorithms with respect to iteration number. by Erdal Eker (19251018)

    Published 2025
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  11. 11
    Strong-noise pixel denoising process schematic.

    Strong-noise pixel denoising process schematic. by Haiyan Zhang (176919)

    Published 2025
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  12. 12
    Weak-noise pixel denoising process schematic.

    Weak-noise pixel denoising process schematic. by Haiyan Zhang (176919)

    Published 2025
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  13. 13
    Algorithm 3: gc_soma.

    Algorithm 3: gc_soma. by Mizuki Kato (5557610)

    Published 2023
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  14. 14
    Algorithm 6: Dendritic elongation.

    Algorithm 6: Dendritic elongation. by Mizuki Kato (5557610)

    Published 2023
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  15. 15
    Adopted parameter ranges and the obtained best parameters via different algorithms.

    Adopted parameter ranges and the obtained best parameters via different algorithms. by Erdal Eker (19251018)

    Published 2025
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  16. 16
    Statistical performance evaluation of algorithms and p-values obtained from Wilcoxon’s test.

    Statistical performance evaluation of algorithms and p-values obtained from Wilcoxon’s test. by Erdal Eker (19251018)

    Published 2025
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  17. 17
    Simulation parameters.

    Simulation parameters. by Faheem Nawaz Tareen (18319868)

    Published 2024
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  18. 18
    KNN algorithm flowchart.

    KNN algorithm flowchart. by Guilian Feng (18530806)

    Published 2024
    “…In order to improve the efficiency and accuracy of high-dimensional data processing, a feature selection method based on optimized genetic algorithm is proposed in this study. …”
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  19. 19
    MGA algorithm flowchart.

    MGA algorithm flowchart. by Guilian Feng (18530806)

    Published 2024
    “…In order to improve the efficiency and accuracy of high-dimensional data processing, a feature selection method based on optimized genetic algorithm is proposed in this study. …”
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  20. 20
    All eigenvalues for all simulations for each casualty source rate.

    All eigenvalues for all simulations for each casualty source rate. by James Hogg (5211725)

    Published 2019
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