Search alternatives:
codon optimization » wolf optimization (Expand Search)
primary data » primary care (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based codon » based color (Expand Search), based cohort (Expand Search), based action (Expand Search)
data swarm » data share (Expand Search)
Showing 1 - 20 results of 36 for search '(( primary data swarm optimization algorithm ) OR ( binary based codon optimization algorithm ))', query time: 1.04s Refine Results
  1. 1
    Iterative optimization convergence curve of each algorithm.

    Iterative optimization convergence curve of each algorithm. by Guangwei Liu (181992)

    Published 2023
    Save to List
    Saved in:
  2. 2
    The optimization results of each algorithm for the 8 benchmark functions.

    The optimization results of each algorithm for the 8 benchmark functions. by Guangwei Liu (181992)

    Published 2023
    Save to List
    Saved in:
  3. 3
    Optimal results of the different algorithms on the speed design reducer problem.

    Optimal results of the different algorithms on the speed design reducer problem. by Guangwei Liu (181992)

    Published 2023
    Save to List
    Saved in:
  4. 4
    Optimal results of the different algorithms on the pressure vessel design problem.

    Optimal results of the different algorithms on the pressure vessel design problem. by Guangwei Liu (181992)

    Published 2023
    Save to List
    Saved in:
  5. 5
    Optimal results of the different algorithms on the gear train design problem.

    Optimal results of the different algorithms on the gear train design problem. by Guangwei Liu (181992)

    Published 2023
    Save to List
    Saved in:
  6. 6
    The optimization results of each algorithm for the CEC2019 benchmark functions.

    The optimization results of each algorithm for the CEC2019 benchmark functions. by Guangwei Liu (181992)

    Published 2023
    Save to List
    Saved in:
  7. 7
    Optimal results of the different algorithms on the tension/compression spring design problem.

    Optimal results of the different algorithms on the tension/compression spring design problem. by Guangwei Liu (181992)

    Published 2023
    Save to List
    Saved in:
  8. 8
    DataSheet1_Optimal capacity configuration of the wind-storage combined frequency regulation system considering secondary frequency drop.docx

    DataSheet1_Optimal capacity configuration of the wind-storage combined frequency regulation system considering secondary frequency drop.docx by Dongdong Li (123985)

    Published 2023
    Save to List
    Saved in:
  9. 9
    S1 Data -

    S1 Data - by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:
  10. 10
    Curve of step response signal of 6 algorithms.

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

    Published 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. …”
    Save to List
    Saved in:
  11. 11
    Data Sheet 1_AI-driven optimization of dynamic vibration absorbers with hydraulic amplifier and mechanical inerter integration.pdf

    Data Sheet 1_AI-driven optimization of dynamic vibration absorbers with hydraulic amplifier and mechanical inerter integration.pdf by Ahmed Shamseldin (19759437)

    Published 2024
    Save to List
    Saved in:
  12. 12
    Wilcoxon’s rank sum test results.

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

    Published 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. …”
    Save to List
    Saved in:
  13. 13
    Flowchart of MSHHOTSA.

    Flowchart of MSHHOTSA. by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:
  14. 14
    Tension/compression spring design problem.

    Tension/compression spring design problem. by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:
  15. 15
    Speed reducer design problem.

    Speed reducer design problem. by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:
  16. 16
    Flowchart of TSA [43].

    Flowchart of TSA [43]. by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:
  17. 17
    Pressure vessel design problem.

    Pressure vessel design problem. by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:
  18. 18
    Gear train design problem.

    Gear train design problem. by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:
  19. 19
    The proportion integral derivative controller.

    The proportion integral derivative controller. by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:
  20. 20
    Random parameter factor.

    Random parameter factor. by Guangwei Liu (181992)

    Published 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. …”
    Save to List
    Saved in:

Search Tools: