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Showing 121 - 140 results of 143 for search '(( binary task design optimization algorithm ) OR ( binary based design optimization algorithm ))*', query time: 0.59s Refine Results
  1. 121
    Parameter sensitivity of BIMGO.

    Parameter sensitivity of BIMGO. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  2. 122
    Details of the medical datasets.

    Details of the medical datasets. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  3. 123
    The flowchart of IMGO.

    The flowchart of IMGO. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  4. 124
    Comparison in terms of the selected features.

    Comparison in terms of the selected features. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  5. 125
    Iterative chart of control factor.

    Iterative chart of control factor. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  6. 126
    Details of 23 basic benchmark functions.

    Details of 23 basic benchmark functions. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  7. 127
    Related researches.

    Related researches. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  8. 128
    S1 Dataset -

    S1 Dataset - by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  9. 129
    Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf

    Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf by Maliheh Aramon (6557906)

    Published 2019
    “…<p>The Fujitsu Digital Annealer is designed to solve fully connected quadratic unconstrained binary optimization (QUBO) problems. …”
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  10. 130
    Summary of LITNET-2020 dataset.

    Summary of LITNET-2020 dataset. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  11. 131
    SHAP analysis for LITNET-2020 dataset.

    SHAP analysis for LITNET-2020 dataset. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  12. 132
    Comparison of intrusion detection systems.

    Comparison of intrusion detection systems. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  13. 133
    Parameter setting for CBOA and PSO.

    Parameter setting for CBOA and PSO. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  14. 134
    NSL-KDD dataset description.

    NSL-KDD dataset description. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  15. 135
    The architecture of LSTM cell.

    The architecture of LSTM cell. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  16. 136
    The architecture of ILSTM.

    The architecture of ILSTM. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  17. 137
    Parameter setting for LSTM.

    Parameter setting for LSTM. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  18. 138
    LITNET-2020 data splitting approach.

    LITNET-2020 data splitting approach. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  19. 139
    Transformation of symbolic features in NSL-KDD.

    Transformation of symbolic features in NSL-KDD. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
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  20. 140
    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf

    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

    Published 2020
    “…In this way, for each binary problem, the CSP algorithm produces features to determine if the specific body part is engaged in the task or not. …”
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