يعرض 101 - 120 نتائج من 173 نتيجة بحث عن '(( binary a global optimization algorithm ) OR ( binary a process optimization algorithm ))', وقت الاستعلام: 0.37s تنقيح النتائج
  1. 101

    Training losses for N = 10. حسب Hend Bayoumi (22693738)

    منشور في 2025
    "…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …"
  2. 102

    Normalized computation rate for N = 10. حسب Hend Bayoumi (22693738)

    منشور في 2025
    "…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …"
  3. 103

    Summary of Notations Used in this paper. حسب Hend Bayoumi (22693738)

    منشور في 2025
    "…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …"
  4. 104
  5. 105

    Wilcoxon test results for feature selection. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
  6. 106

    Feature selection metrics and their definitions. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
  7. 107

    Statistical summary of all models. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
  8. 108

    Feature selection results. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
  9. 109

    ANOVA test for feature selection. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
  10. 110

    Classification performance of ML and DL models. حسب Amal H. Alharbi (21755906)

    منشور في 2025
    "…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"
  11. 111
  12. 112

    Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles حسب Peter S. Rice (11805875)

    منشور في 2025
    "…For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe<sub>182</sub>C<sub>88</sub> NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). …"
  13. 113
  14. 114

    Dynamic resource allocation process. حسب Yixian Wen (12201388)

    منشور في 2025
    "…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
  15. 115

    Event-driven data flow processing. حسب Yixian Wen (12201388)

    منشور في 2025
    "…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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  20. 120

    Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. حسب Jiaqing Luo (10975030)

    منشور في 2021
    "…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …"