Showing 1 - 20 results of 30 for search '(( gene based action optimization algorithm ) OR ( binary based swarm optimization algorithm ))', query time: 1.00s Refine Results
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    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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    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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    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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    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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    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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    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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    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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    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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    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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    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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    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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    Raw Data for the Thesis: "<i>Enhancing RNAi-Based Pest Control through Effective Target Gene Selection and Optimal dsRNA Design</i>" by Doga CEDDEN (12675286)

    Published 2025
    “…</p><p><br></p><p dir="ltr">Chapter 4 introduces the dsRIP web platform (<a href="https://dsrip.uni-goettingen.de/" target="_blank">https://dsrip.uni-goettingen.de/</a>) for designing sequence-optimized dsRNA for RNAi-based pest control. In the experimental part, small interfering RNA (siRNA) features that were associated with RNAi efficacy in human cells were tested in <i>T. castaneum </i>by targeting an essential gene and measuring insecticidal efficacy. …”
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    Gex2SGen: Designing Drug-like Molecules from Desired Gene Expression Signatures by Dibyajyoti Das (14845321)

    Published 2023
    “…Most importantly, this knowledge can be used to discover drugs’ mechanisms of action. Recently, deep learning-based drug design methods are in the spotlight due to their ability to explore huge chemical space and design property-optimized target-specific drug molecules. …”
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    Gex2SGen: Designing Drug-like Molecules from Desired Gene Expression Signatures by Dibyajyoti Das (14845321)

    Published 2023
    “…Most importantly, this knowledge can be used to discover drugs’ mechanisms of action. Recently, deep learning-based drug design methods are in the spotlight due to their ability to explore huge chemical space and design property-optimized target-specific drug molecules. …”
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    Gex2SGen: Designing Drug-like Molecules from Desired Gene Expression Signatures by Dibyajyoti Das (14845321)

    Published 2023
    “…Most importantly, this knowledge can be used to discover drugs’ mechanisms of action. Recently, deep learning-based drug design methods are in the spotlight due to their ability to explore huge chemical space and design property-optimized target-specific drug molecules. …”