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Showing 1 - 20 results of 41 for search '(( binary based driven optimization algorithm ) OR ( library based case optimization algorithm ))', query time: 0.51s 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
    Library of the 55 different classification and regression machine-learning algorithms used by the ensemble predictor SuperLearner (SL.library) in the CBDA 2.0 implementation.

    Library of the 55 different classification and regression machine-learning algorithms used by the ensemble predictor SuperLearner (SL.library) in the CBDA 2.0 implementation. by Simeone Marino (81051)

    Published 2020
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  3. 3
    Summary of classification algorithms.

    Summary of classification algorithms. by Stephen R. Piccolo (8367780)

    Published 2022
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  4. 4
    An optimal solution for the HFS instance.

    An optimal solution for the HFS instance. by Xiang Tian (4369285)

    Published 2025
    “…Next, a CP model (IPMMPO-CP) applicable to multi-scenario HFS problems is proposed. Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
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  5. 5
    Summary of feature-selection algorithms.

    Summary of feature-selection algorithms. by Stephen R. Piccolo (8367780)

    Published 2022
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  6. 6
    Relative classification performance per combination of feature-selection and classification algorithm.

    Relative classification performance per combination of feature-selection and classification algorithm. by Stephen R. Piccolo (8367780)

    Published 2022
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  7. 7
    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start

    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start by Yifan Wang (380120)

    Published 2025
    “…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …”
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  8. 8
    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start

    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start by Yifan Wang (380120)

    Published 2025
    “…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …”
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  9. 9
    Relative predictive performance when using default algorithm hyperparameters and all features vs. tuning hyperparameters or selecting features.

    Relative predictive performance when using default algorithm hyperparameters and all features vs. tuning hyperparameters or selecting features. by Stephen R. Piccolo (8367780)

    Published 2022
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  10. 10
    Comparison based on hard instances from [79].

    Comparison based on hard instances from [79]. by Xiang Tian (4369285)

    Published 2025
    “…Next, a CP model (IPMMPO-CP) applicable to multi-scenario HFS problems is proposed. Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
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  11. 11
    Schematic diagram of the Dropout optimization.

    Schematic diagram of the Dropout optimization. by Peng Yang (296696)

    Published 2024
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  12. 12
    Relative predictive performance when training on gene-expression predictors alone vs. using clinical predictors alone or gene-expression predictors in combination with clinical predictors.

    Relative predictive performance when training on gene-expression predictors alone vs. using clinical predictors alone or gene-expression predictors in combination with clinical pre... by Stephen R. Piccolo (8367780)

    Published 2022
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  13. 13
    Hierarchical Optimization on large models.

    Hierarchical Optimization on large models. by Nisha Ann Viswan (20371285)

    Published 2024
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  14. 14
    the functioning of BRPSO.

    the functioning of BRPSO. by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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  15. 15
    Characteristic of 6- and 10-story SMRF [99,98].

    Characteristic of 6- and 10-story SMRF [99,98]. by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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  16. 16
    The RFD’s behavior mechanism (2002).

    The RFD’s behavior mechanism (2002). by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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  17. 17
    A simple HFS instance.

    A simple HFS instance. by Xiang Tian (4369285)

    Published 2025
    “…Next, a CP model (IPMMPO-CP) applicable to multi-scenario HFS problems is proposed. Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
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  18. 18
    The scheduling Gantt chart.

    The scheduling Gantt chart. by Xiang Tian (4369285)

    Published 2025
    “…Next, a CP model (IPMMPO-CP) applicable to multi-scenario HFS problems is proposed. Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
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  19. 19
    Structure and computational framework of IPMMPO.

    Structure and computational framework of IPMMPO. by Xiang Tian (4369285)

    Published 2025
    “…Next, a CP model (IPMMPO-CP) applicable to multi-scenario HFS problems is proposed. Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
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  20. 20
    Data types contained in and .

    Data types contained in and . by Xiang Tian (4369285)

    Published 2025
    “…Next, a CP model (IPMMPO-CP) applicable to multi-scenario HFS problems is proposed. Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
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