Showing 1 - 20 results of 33 for search '(( lens based model optimization algorithm ) OR ( binary change models optimization algorithm ))', query time: 0.47s Refine Results
  1. 1

    Lens imaging opposition-based learning. by Yuqi Xiong (12343771)

    Published 2025
    “…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …”
  2. 2
  3. 3
  4. 4

    Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens by Hee-Jae Jeon (4614121)

    Published 2021
    “…Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. …”
  5. 5

    Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens by Hee-Jae Jeon (4614121)

    Published 2021
    “…Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. …”
  6. 6
  7. 7

    Compare algorithm parameter settings. by Yuqi Xiong (12343771)

    Published 2025
    “…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …”
  8. 8
  9. 9
  10. 10
  11. 11

    -value on CEC2022 (dim = 20). by Yuqi Xiong (12343771)

    Published 2025
    “…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …”
  12. 12

    Precision elimination strategy. by Yuqi Xiong (12343771)

    Published 2025
    “…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …”
  13. 13

    Results of low-light image enhancement test. by Yuqi Xiong (12343771)

    Published 2025
    “…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …”
  14. 14

    -value on 23 benchmark functions (dim = 30). by Yuqi Xiong (12343771)

    Published 2025
    “…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …”
  15. 15

    Evaluation metrics obtained by SBOA and MESBOA. by Yuqi Xiong (12343771)

    Published 2025
    “…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …”
  16. 16
  17. 17
  18. 18

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

    Published 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). …”
  19. 19

    Confusion matrix. by Yixian Wen (12201388)

    Published 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. …”
  20. 20

    Parameter settings. by Yixian Wen (12201388)

    Published 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. …”