يعرض 101 - 120 نتائج من 3,171 نتيجة بحث عن '(( algorithm both function ) OR ((( algorithm python function ) OR ( algorithm pre function ))))', وقت الاستعلام: 0.53s تنقيح النتائج
  1. 101
  2. 102

    PathOlOgics_RBCs Python Scripts.zip حسب Ahmed Elsafty (16943883)

    منشور في 2023
    "…<p dir="ltr">The first algorithm for segmentation and localization (see PathOlOgics_script_1; segment & localize using a pen) relied on manually tracing the borders of each cell using a digital pen tool on a big touchscreen display showing source images/patches. …"
  3. 103

    Algorithm of the brightness scale calibration experiment. حسب Krzysztof Petelczyc (3954203)

    منشور في 2024
    "…<p>In the algorithm, the following variables were used: “I” denotes the current luminous intensity of the reference diode, “inc” denotes the current difference between reference and target diode luminous intensity; “cnt” is the current number of performed trials, while “correct” is a counter of correct answers in cnt trials, both of them are counted separately for every settings of I and inc. …"
  4. 104

    Gillespie algorithm simulation parameters. حسب Nicholas H. Vitale (20469289)

    منشور في 2024
    "…Both the ensemble and stochastic models presented in this work have been verified using Monte Carlo molecular dynamic simulations that utilize the Gillespie algorithm. …"
  5. 105

    Scheduling time of five algorithms. حسب Huichao Guo (14515171)

    منشور في 2025
    "…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
  6. 106

    Convergence speed of five algorithms. حسب Huichao Guo (14515171)

    منشور في 2025
    "…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
  7. 107
  8. 108

    Multi-algorithm comparison figure. حسب Dawei Wang (471687)

    منشور في 2025
    "…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …"
  9. 109

    Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy حسب Yujin Wu (2901128)

    منشور في 2021
    "…We also describe a novel hybrid searching algorithm that combines both molecular dynamics (MD)-based simulated annealing and genetic algorithm crossovers to address the enhanced sampling of the increased search space. …"
  10. 110

    Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy حسب Yujin Wu (2901128)

    منشور في 2021
    "…We also describe a novel hybrid searching algorithm that combines both molecular dynamics (MD)-based simulated annealing and genetic algorithm crossovers to address the enhanced sampling of the increased search space. …"
  11. 111

    A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases حسب Maru Song (22593561)

    منشور في 2025
    "…Crucially, we propose fitness functions based on approximate measures of the wave function compactness, which enable inexpensive genetic algorithm searches. …"
  12. 112
  13. 113

    Completion times for different algorithms. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …"
  14. 114

    The average cumulative reward of algorithms. حسب Jianbin Zheng (587000)

    منشور في 2025
    "…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …"
  15. 115

    Both Ankle fNIRS MI dataset حسب Hammad Gilani (8060012)

    منشور في 2025
    "…<p><br></p><p dir="ltr">This dataset contains functional near-infrared spectroscopy (fNIRS) signals recorded during motor imagery (MI) tasks of lower limb movements. …"
  16. 116

    AUC scores of anomaly detection algorithms. حسب GaoXiang Zhao (21499525)

    منشور في 2025
    "…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …"
  17. 117

    Recall scores of anomaly detection algorithms. حسب GaoXiang Zhao (21499525)

    منشور في 2025
    "…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …"
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    Python implementation from Symplectic decomposition from submatrix determinants حسب Jason L. Pereira (11598632)

    منشور في 2021
    "…Python implementation of the algorithm and demonstration of how to use the functions.…"