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Showing 1 - 8 results of 8 for search '(( binary based bayesian optimization algorithm ) OR ( binary data wolf optimization algorithm ))*', query time: 0.35s Refine Results
  1. 1
    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things

    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
    “…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
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  2. 2
    The flowchart of the proposed algorithm.

    The flowchart of the proposed algorithm. by Muhammad Ayyaz Sheikh (18610943)

    Published 2024
    “…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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  3. 3
    Bayesian sequential design for sensitivity experiments with hybrid responses

    Bayesian sequential design for sensitivity experiments with hybrid responses by Yuxia Liu (1779592)

    Published 2023
    “…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …”
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  4. 4
    Summary of literature review.

    Summary of literature review. by Muhammad Ayyaz Sheikh (18610943)

    Published 2024
    “…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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  5. 5
    Topic description.

    Topic description. by Muhammad Ayyaz Sheikh (18610943)

    Published 2024
    “…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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  6. 6
    Notations along with their descriptions.

    Notations along with their descriptions. by Muhammad Ayyaz Sheikh (18610943)

    Published 2024
    “…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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  7. 7
    Detail of the topics extracted from DUC2002.

    Detail of the topics extracted from DUC2002. by Muhammad Ayyaz Sheikh (18610943)

    Published 2024
    “…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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  8. 8
    Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf

    Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

    Published 2024
    “…Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”
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