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Showing 81 - 100 results of 692 for search '(( algorithm state function ) OR ( algorithm python function ))*', query time: 0.33s Refine Results
  1. 81
    Escape coefficient (R) and escape strategy probability threshold (Ps) hybrid functions analysis.

    Escape coefficient (R) and escape strategy probability threshold (Ps) hybrid functions analysis. by Tengfei Ma (597633)

    Published 2025
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  2. 82
    Escape coefficient (R) and escape strategy probability threshold (Ps) composition functions analysis.

    Escape coefficient (R) and escape strategy probability threshold (Ps) composition functions analysis. by Tengfei Ma (597633)

    Published 2025
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  3. 83
    Q-Learning state definition based on objective medians.

    Q-Learning state definition based on objective medians. by Zhongfeng Li (3965060)

    Published 2025
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  4. 84
    A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.

    A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finit... by Hassan Mehboob (8960273)

    Published 2025
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  5. 85
    (a) Comparison between SDNN and Traditional Methods. The horizontal axis represents the prediction horizon, while the vertical axis denotes computation time; red denotes traditional methods, and blue represents SDNN. (b) Comparison of different algorithms under different inputs. The horizontal axis represents algorithm type and total surrounding computation speed, with red lines indicating single input and blue lines representing multiple inputs.

    (a) Comparison between SDNN and Traditional Methods. The horizontal axis represents the prediction horizon, while the vertical axis denotes computation time; red denotes traditiona... by Kai Sun (140584)

    Published 2025
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  6. 86
    Corresponding Markov Chain Model representing the probability of quantum state transition over an infinitesimal time step.

    Corresponding Markov Chain Model representing the probability of quantum state transition over an infinitesimal time step. by Nicholas H. Vitale (20469289)

    Published 2024
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  7. 87
    Parameters to configure the multi-staged vascularization using the PDCCO algorithm.

    Parameters to configure the multi-staged vascularization using the PDCCO algorithm. by Eduardo G. Zilves (22209247)

    Published 2025
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  8. 88
    The iterative process of genetic algorithm in the upper-level model.

    The iterative process of genetic algorithm in the upper-level model. by Zhipeng Huang (1759759)

    Published 2025
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  9. 89
    IEEE CEC 2017 benchmark function specifications.

    IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

    Published 2025
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  10. 90
    IEEE CEC 2022 benchmark function specifications.

    IEEE CEC 2022 benchmark function specifications. by Kankan Tang (21474968)

    Published 2025
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  11. 91
    Code snippets to add user-specific custom functionality in PyNoetic.

    Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

    Published 2025
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  12. 92
    System no-load torque response results under three control algorithms.

    System no-load torque response results under three control algorithms. by Haoran Cui (7235234)

    Published 2024
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  13. 93
    Path data for different algorithms in four different environments.

    Path data for different algorithms in four different environments. by Tengfei Ma (597633)

    Published 2025
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  14. 94
    Modular architecture design of PyNoetic showing all its constituent functions.

    Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

    Published 2025
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  15. 95
    Wilcoxon p-value of the en-CSA vs baseline algorithms for CEC2020.

    Wilcoxon p-value of the en-CSA vs baseline algorithms for CEC2020. by Sarah A. Alzakari (19704611)

    Published 2024
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  16. 96
    Schematic diagram of sliding mode variable structure control algorithm design content.

    Schematic diagram of sliding mode variable structure control algorithm design content. by Haoran Cui (7235234)

    Published 2024
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  17. 97
    Trainable parameters for different algorithms.

    Trainable parameters for different algorithms. by Anwar Hossain Efat (19942283)

    Published 2024
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  18. 98
    Parameters and variables used to generalized cost function.

    Parameters and variables used to generalized cost function. by Zhipeng Huang (1759759)

    Published 2025
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  19. 99
    Depiction of the two possible quenched (hairpin) and unquenched (random coil) conformational states ssDNA can switch between at equilibrium.

    Depiction of the two possible quenched (hairpin) and unquenched (random coil) conformational states ssDNA can switch between at equilibrium. by Nicholas H. Vitale (20469289)

    Published 2024
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  20. 100
    Neuron by neuron comparison of correlation coefficient for the state-of-the-art methods STM and Oasis.

    Neuron by neuron comparison of correlation coefficient for the state-of-the-art methods STM and Oasis. by Nicholas A. Rondoni (21573261)

    Published 2025
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