Showing 81 - 100 results of 15,685 for search '(( algorithm python function ) OR ((( algorithm its function ) OR ( algorithm a function ))))*', query time: 1.68s Refine Results
  1. 81

    Algorithm ranking under different dimensions. by Wei Liu (20030)

    Published 2023
    “…The results show: (1) the global convergence probability of SGWO was 1, and its process was a finite homogeneous Markov chain with an absorption state; (2) SGWO not only has better optimization performance when solving complex functions of different dimensions, but also when applied to Elman for parameter optimization, SGWO can significantly optimize the network structure and SGWO-Elman has accurate prediction performance.…”
  2. 82

    Parameter sets of the chosen algorithms. by WanRu Zhao (18980374)

    Published 2024
    “…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”
  3. 83

    The flow chart of IERWHO algorithm. by WanRu Zhao (18980374)

    Published 2024
    “…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”
  4. 84

    The flow chart of WHO algorithm. by WanRu Zhao (18980374)

    Published 2024
    “…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”
  5. 85

    CEC2017 test function test results. by Tengfei Ma (597633)

    Published 2025
    “…<div><p>To address the limitations of the Zebra Optimization Algorithm (ZOA), including insufficient late-stage optimization search capability, susceptibility to local optima, slow convergence, and inadequate exploration, this paper proposes an enhanced Zebra Optimization Algorithm integrating opposition-based learning and a dynamic elite-pooling strategy (OP-ZOA: Opposition-Based Learning Dynamic Elite-Pooling Zebra Optimization Algorithm). he proposed search algorithm employs a good point set-elite opposition-based learning mechanism to initialize the population, enhancing diversity and facilitating escape from local optima. …”
  6. 86

    Compare algorithm parameter settings. by Yuqi Xiong (12343771)

    Published 2025
    “…<div><p>Metaheuristic optimization algorithms often face challenges such as complex modeling, limited adaptability, and a tendency to get trapped in local optima when solving complex optimization problems. …”
  7. 87

    Flowchart of the specific incarnation of the BO algorithm used in the experiments. by Lisa Laux (9367681)

    Published 2020
    “…To choose the next pipeline configuration to evaluate, the BO algorithm uses an Expected Improvement function to trade off maximisation of QS with the need to fully learn the GP. …”
  8. 88

    Description of unimodal benchmark functions. by Yi-Qiang Xia (20161326)

    Published 2024
    “…In essence, it prevents algorithms from settling for suboptimal solutions too soon, encouraging exploration of a broader solution space before converging, by incorporating cauchy variation and a perturbation term, MWOA achieve optimization over a wide search space. …”
  9. 89

    Description of multimodal benchmark functions. by Yi-Qiang Xia (20161326)

    Published 2024
    “…In essence, it prevents algorithms from settling for suboptimal solutions too soon, encouraging exploration of a broader solution space before converging, by incorporating cauchy variation and a perturbation term, MWOA achieve optimization over a wide search space. …”
  10. 90
  11. 91

    Statistical results of various algorithms. by ZeSheng Lin (20501356)

    Published 2025
    “…In order to effectively handle extensive datasets, researchers have introduced diverse classification algorithms. Notably, Kernel Extreme Learning Machine (KELM), as a fast and effective classification method, has received widespread attention. …”
  12. 92
  13. 93
  14. 94

    Images of partial benchmark functions. by ZeSheng Lin (20501356)

    Published 2025
    “…In order to effectively handle extensive datasets, researchers have introduced diverse classification algorithms. Notably, Kernel Extreme Learning Machine (KELM), as a fast and effective classification method, has received widespread attention. …”
  15. 95

    Iteration curves of different algorithms. by Tengfei Ma (597633)

    Published 2025
    “…<div><p>To address the limitations of the Zebra Optimization Algorithm (ZOA), including insufficient late-stage optimization search capability, susceptibility to local optima, slow convergence, and inadequate exploration, this paper proposes an enhanced Zebra Optimization Algorithm integrating opposition-based learning and a dynamic elite-pooling strategy (OP-ZOA: Opposition-Based Learning Dynamic Elite-Pooling Zebra Optimization Algorithm). he proposed search algorithm employs a good point set-elite opposition-based learning mechanism to initialize the population, enhancing diversity and facilitating escape from local optima. …”
  16. 96

    Flowchart of OP-ZOA algorithm. by Tengfei Ma (597633)

    Published 2025
    “…<div><p>To address the limitations of the Zebra Optimization Algorithm (ZOA), including insufficient late-stage optimization search capability, susceptibility to local optima, slow convergence, and inadequate exploration, this paper proposes an enhanced Zebra Optimization Algorithm integrating opposition-based learning and a dynamic elite-pooling strategy (OP-ZOA: Opposition-Based Learning Dynamic Elite-Pooling Zebra Optimization Algorithm). he proposed search algorithm employs a good point set-elite opposition-based learning mechanism to initialize the population, enhancing diversity and facilitating escape from local optima. …”
  17. 97

    MChOA algorithm flow chart. by Guilin Yang (583364)

    Published 2024
    “…<div><p>To address the issue of poor performance in the chimp optimization (ChOA) algorithm, a new algorithm called the manta ray-based chimpa optimization algorithm (MChOA) was developed. …”
  18. 98

    If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

    Published 2024
    “…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”
  19. 99

    Data_Sheet_3_Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways.csv by Maxim Sorokin (4379848)

    Published 2021
    “…We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. …”
  20. 100

    Data_Sheet_2_Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways.pdf by Maxim Sorokin (4379848)

    Published 2021
    “…We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. …”