بدائل البحث:
design optimization » bayesian optimization (توسيع البحث)
sample design » sampling design (توسيع البحث)
binary more » binary image (توسيع البحث)
يعرض 1 - 20 نتائج من 96 نتيجة بحث عن '(( binary more _ optimization algorithm ) OR ( total sample design optimization algorithm ))', وقت الاستعلام: 0.55s تنقيح النتائج
  1. 1

    MSE for ILSTM algorithm in binary classification. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  2. 2
  3. 3

    Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level حسب Giovanni Nattino (561797)

    منشور في 2021
    "…We fill the gap by developing an iterative matching algorithm for the three-group setting. Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …"
  4. 4

    Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple... حسب Yangyang Liu (807797)

    منشور في 2022
    "…Simulation tests reveal that the dynamic genetic algorithm with ant colony binary iterative optimization (DGA-ACBIO) proposed in this study shortens the optimal flight range by 715.8 m, 428.3 m, 589 m, and 287.6 m compared to the dynamic genetic algorithm, ant colony binary iterative algorithm, artificial fish swarm algorithm (AFSA) and particle swarm optimization (PSO), respectively, for multiple tea field scheduling route planning. …"
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9

    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب Se-Hee Jo (20554623)

    منشور في 2025
    "…The percentage mean absolute residuals of the activity coefficients obtained using DEA, NMM, and the parameter estimation tool in Aspen Plus were in the ranges of 0.05–16.69, 0.05–16.69, and 0.09–326.77%, respectively. This in-house algorithm will be helpful for obtaining more accurate NRTL parameters in a timely manner and will facilitate the simulation of biochemical processes for process optimization, energy consumption estimation, and life cycle assessment.…"
  10. 10
  11. 11
  12. 12

    The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  13. 13

    IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  14. 14

    IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  15. 15
  16. 16

    Free vibration analysis and optimal design of adhesively bonded double-strap joints by using artificial neural networks حسب Qi Guo (133147)

    منشور في 2021
    "…The effects of the adhesive material properties and joint geometrical parameters on the joint dynamic characteristics were investigated in detail using the trained ANNs. The optimum design problem is defined as a multi-objective optimization problem considering maximizing the first natural frequency and corresponding loss factor while minimizing the total structural weight. …"
  17. 17

    Optimal contrast analysis with heterogeneous variances and budget concerns حسب Show-Li Jan (3538697)

    منشور في 2019
    "…Optimal allocation procedures for the Welch-Satterthwaite tests of standardized and unstandardized contrasts are presented to minimize the total sample size with the designated ratios, to meet a desirable power level for the least cost, and to attain the maximum power performance under a fixed cost. …"
  18. 18

    Hyperparameters of the LSTM Model. حسب Ahmed M. Elshewey (21463867)

    منشور في 2025
    "…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"
  19. 19

    The AD-PSO-Guided WOA LSTM framework. حسب Ahmed M. Elshewey (21463867)

    منشور في 2025
    "…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"
  20. 20

    Prediction results of individual models. حسب Ahmed M. Elshewey (21463867)

    منشور في 2025
    "…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"