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Showing 41 - 55 results of 55 for search '(( binary paper based optimization algorithm ) OR ( binary pairs based optimization algorithm ))', query time: 0.28s Refine Results
  1. 41
  2. 42

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

    Published 2023
    “…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. …”
  3. 43

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

    Published 2023
    “…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. …”
  4. 44

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

    Published 2023
    “…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. …”
  5. 45

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

    Published 2023
    “…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. …”
  6. 46

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

    Published 2023
    “…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. …”
  7. 47

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

    Published 2023
    “…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. …”
  8. 48

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

    Published 2023
    “…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. …”
  9. 49

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

    Published 2023
    “…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. …”
  10. 50

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

    Published 2023
    “…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. …”
  11. 51

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

    Published 2023
    “…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. 53

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

    Published 2020
    “…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”
  14. 54

    Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP by Xiaofeng Wang (119575)

    Published 2021
    “…In this study, we propose a novel prediction model based on optimization algorithm and neural network, which can select and rank the most important factors that affect mental health of medical workers. …”
  15. 55

    Seed mix selection model by Bethanne Bruninga-Socolar (10923639)

    Published 2022
    “…The model thus requires three types of data presented as matrices in order to calculate the maximum number of bee species supported by a given seed mix: 1) adult phenology of each bee species, where each cell represents whether or not that bee species was observed in the data during a given time period, 2) flowering phenology of plants, where each cell represents whether or not a bee was collected from that plant species during a given time period, and 3) pairwise interactions between plant species and bee species, where each cell represents whether each plant-bee species pair was observed interacting in the data.</p> <p>  </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”