Showing 21 - 40 results of 44 for search '(( binary a resource optimization algorithm ) OR ( binary data wolf optimization algorithm ))*', query time: 0.54s Refine Results
  1. 21

    Wilcoxon test results for optimization. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
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    Wilcoxon test results for feature selection. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  5. 25

    Feature selection metrics and their definitions. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  6. 26

    Statistical summary of all models. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  7. 27

    Feature selection results. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  8. 28

    ANOVA test for feature selection. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  9. 29

    Classification performance of ML and DL models. by Amal H. Alharbi (21755906)

    Published 2025
    “…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
  10. 30

    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. …”
  11. 31

    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. …”
  12. 32

    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. …”
  13. 33

    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. …”
  14. 34

    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. …”
  15. 35

    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. …”
  16. 36

    Event-driven data flow processing. 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. …”
  17. 37

    Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity by George S. Watts (7962206)

    Published 2019
    “…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. …”
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    MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

    Published 2025
    “…This paper presents a quantum computing path for Transformation-to-Sampling-to-Verification of geospatial optimization problems, adaptable to the controlled qubit scale and coherence constraints under current NISQ conditions. …”
  20. 40

    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. …”