يعرض 21 - 40 نتائج من 64 نتيجة بحث عن '(( laboratory tests process optimization algorithm ) OR ( binary a while optimization algorithm ))', وقت الاستعلام: 0.32s تنقيح النتائج
  1. 21

    the functioning of BRPSO. حسب Hossein Jarrahi (22530251)

    منشور في 2025
    "…The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …"
  2. 22

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

    منشور في 2025
    "…The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …"
  3. 23

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

    منشور في 2025
    "…The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …"
  4. 24

    Estimating CO2-Brine diffusivity using hybrid models of ANFIS and evolutionary algorithms حسب Amin Bemani (9287205)

    منشور في 2020
    "…The R<sup>2</sup> values forthe testing phase are 0.9978, 0.9932, 0.9854, 0.9738 and 0.9514 for ANFIS optimized by particle swarm optimization (PSO), genetic algorithms (GA), ant colony optimization (ACO), backpropagation (BP), and differential evolution (DE), respectively. …"
  5. 25

    Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf حسب Muhammad Awais (263096)

    منشور في 2024
    "…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"
  6. 26

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  7. 27

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  8. 28

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  9. 29

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  10. 30

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  11. 31

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  12. 32

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  13. 33

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  14. 34

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
  15. 35

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

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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  17. 37

    Generalized Tensor Decomposition With Features on Multiple Modes حسب Jiaxin Hu (1327875)

    منشور في 2021
    "…Our proposal handles a broad range of data types, including continuous, count, and binary observations. …"
  18. 38

    Video-to-Model Data Set حسب Sönke Knoch (8616117)

    منشور في 2020
    "…</div><div><br></div><div>Abstract: Manual activities are often hidden deep down in discrete manufacturing processes. For the elicitation and optimization of process behavior, complete information about the execution of Manual activities are required. …"
  19. 39

    Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity حسب George S. Watts (7962206)

    منشور في 2019
    "…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. Binary mixtures of bacteria showed all three reliably identified organisms down to 1% relative abundance, while only the relative abundance estimates of Centrifuge and CLARK were accurate. …"
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