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Showing 1 - 20 results of 36 for search '(( genes based codon optimization algorithm ) OR ( binary based swarm optimization algorithm ))', query time: 0.59s Refine Results
  1. 1
    Comparison between ILSTM and machine learning-based algorithms in binary classification.

    Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
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  2. 2
    Comparison between ILSTM and deep learning-based algorithms in binary classification.

    Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
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  3. 3
    MSE for ILSTM algorithm in binary classification.

    MSE for ILSTM algorithm in binary classification. 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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  4. 4
    Binary encoding scheme.

    Binary encoding scheme. by Binh Thanh Dang (12368831)

    Published 2022
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  5. 5
    Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple tea fields.XLSX

    Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple... by Yangyang Liu (807797)

    Published 2022
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  6. 6
    Table5_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table5_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  7. 7
    Image2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG

    Image2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  8. 8
    Table1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  9. 9
    Image1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG

    Image1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  10. 10
    Image3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG

    Image3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  11. 11
    Table3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  12. 12
    Table4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  13. 13
    Table2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  14. 14
    Image4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG

    Image4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

    Published 2023
    “…For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  15. 15
    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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  16. 16
    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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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    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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