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Showing 141 - 160 results of 350 for search '(( lines based process optimization algorithm ) OR ( binary based based optimization algorithm ))', query time: 0.80s Refine Results
  1. 141
    Small-scale dataset comparative analysis using computation resources.

    Small-scale dataset comparative analysis using computation resources. by Olaide N. Oyelade (14047002)

    Published 2023
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  2. 142
    Small-scale dataset comparative analysis using the number of features selected.

    Small-scale dataset comparative analysis using the number of features selected. by Olaide N. Oyelade (14047002)

    Published 2023
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  3. 143
    A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some small-sized dimensional datasets using a variation of 50 and 100 population sizes.

    A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some small-sized dimensional datas... by Olaide N. Oyelade (14047002)

    Published 2023
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  4. 144
    Large-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100.

    Large-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

    Published 2023
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  5. 145
    Parameter settings.

    Parameter settings. by Olaide N. Oyelade (14047002)

    Published 2023
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  6. 146
    Fig 2 -

    Fig 2 - by Olaide N. Oyelade (14047002)

    Published 2023
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  7. 147
    Flowchart scheme of the ML-based model.

    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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  8. 148
    mAP@0.5 line charts for different models.

    mAP@0.5 line charts for different models. by Meiling Shi (13148944)

    Published 2024
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  9. 149
    Model selection by BO based on RCV(nv) from the simulated data with different noise levels.

    Model selection by BO based on RCV(nv) from the simulated data with different noise levels. by László Zimányi (2649973)

    Published 2021
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  10. 150
    Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files

    Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files by Suchismita Behera (22027316)

    Published 2025
    “…<p dir="ltr">Figures represented here illustrates the <b>metaheuristic-based band selection framework</b> for hyperspectral image classification using <b>Binary Jaya Algorithm enhanced with a mutation operator</b> to improve population diversity and avoid premature convergence. …”
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  11. 151
    A new fast filtering algorithm for a 3D point cloud based on RGB-D information

    A new fast filtering algorithm for a 3D point cloud based on RGB-D information by Chaochuan Jia (7256237)

    Published 2019
    “…This method aligns the color image to the depth image, and the color mapping image is converted to an HSV image. Then, the optimal segmentation threshold of the V image that is calculated by using the Otsu algorithm is applied to segment the color mapping image into a binary image, which is used to extract the valid point cloud from the original point cloud with outliers. …”
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  12. 152
    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment

    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

    Published 2019
    “…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …”
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  13. 153
    Fig 10 -

    Fig 10 - by Shanthi Amgothu (17692146)

    Published 2023
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  14. 154
    Comparative discussion on database-1.

    Comparative discussion on database-1. by Shanthi Amgothu (17692146)

    Published 2023
    “…Here, RNBJSO is the combination of Namib Beetle Optimization (NBO), Remora Optimization Algorithm (ROA) and Jellyfish Search optimization (JSO). …”
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  15. 155
    Schematic view of fog layer.

    Schematic view of fog layer. by Shanthi Amgothu (17692146)

    Published 2023
    “…Here, RNBJSO is the combination of Namib Beetle Optimization (NBO), Remora Optimization Algorithm (ROA) and Jellyfish Search optimization (JSO). …”
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  16. 156
    Simulation parameter.

    Simulation parameter. by Shanthi Amgothu (17692146)

    Published 2023
    “…Here, RNBJSO is the combination of Namib Beetle Optimization (NBO), Remora Optimization Algorithm (ROA) and Jellyfish Search optimization (JSO). …”
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  17. 157
    Systematic model of fog-cloud COVID prediction.

    Systematic model of fog-cloud COVID prediction. by Shanthi Amgothu (17692146)

    Published 2023
    “…Here, RNBJSO is the combination of Namib Beetle Optimization (NBO), Remora Optimization Algorithm (ROA) and Jellyfish Search optimization (JSO). …”
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  18. 158
    Comparative discussion on database-2.

    Comparative discussion on database-2. by Shanthi Amgothu (17692146)

    Published 2023
    “…Here, RNBJSO is the combination of Namib Beetle Optimization (NBO), Remora Optimization Algorithm (ROA) and Jellyfish Search optimization (JSO). …”
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  19. 159
    Solution encoding.

    Solution encoding. by Shanthi Amgothu (17692146)

    Published 2023
    “…Here, RNBJSO is the combination of Namib Beetle Optimization (NBO), Remora Optimization Algorithm (ROA) and Jellyfish Search optimization (JSO). …”
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  20. 160
    Architectural view of DNFN.

    Architectural view of DNFN. by Shanthi Amgothu (17692146)

    Published 2023
    “…Here, RNBJSO is the combination of Namib Beetle Optimization (NBO), Remora Optimization Algorithm (ROA) and Jellyfish Search optimization (JSO). …”
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