Showing 1 - 20 results of 118 for search '(( binary based robust optimization algorithm ) OR ( binary a model optimization algorithm ))', query time: 0.55s Refine Results
  1. 1

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

    Published 2025
    “…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
  2. 2

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

    Published 2025
    “…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
  3. 3

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

    Published 2025
    “…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
  4. 4

    DE algorithm flow. by Ling Zhao (111365)

    Published 2025
    “…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
  5. 5

    Test results of different algorithms. by Ling Zhao (111365)

    Published 2025
    “…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
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    Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

    Published 2024
    “…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …”
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    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
  10. 10

    A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

    Published 2025
    “…Future work aims to generalize this algorithm for broader biological applications by training additional Cellpose models and adapting the A* framework.…”
  11. 11

    Algorithm for generating hyperparameter. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
  12. 12

    Results of machine learning algorithm. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
  13. 13

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

    Published 2025
    “…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”
  14. 14

    ROC comparison of machine learning algorithm. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
  15. 15

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

    Published 2025
    “…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”
  16. 16

    Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

    Published 2025
    “…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”
  17. 17

    Best optimizer results of Lightbgm. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
  18. 18

    Best optimizer results of Adaboost. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
  19. 19

    Best optimizer results of Lightbgm. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
  20. 20

    Random forest with hyperparameter optimization. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”