Showing 241 - 260 results of 718 for search '(((( element method algorithm ) OR ( complement based algorithm ))) OR ( level coding algorithm ))', query time: 0.57s Refine Results
  1. 241

    Flowchart of DBO-BPNN prediction. by Ma Haohao (22177538)

    Published 2025
    “…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”
  2. 242

    Ricker seismic profile. by Zhenjing Yao (22189970)

    Published 2025
    “…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
  3. 243

    Noise reduction on testing sets from STEAD. by Zhenjing Yao (22189970)

    Published 2025
    “…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
  4. 244

    SNR comparison of real-field seismic profile. by Zhenjing Yao (22189970)

    Published 2025
    “…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
  5. 245

    The 147th single trace. by Zhenjing Yao (22189970)

    Published 2025
    “…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
  6. 246
  7. 247
  8. 248
  9. 249

    Video 1_A hybrid elastic-hyperelastic approach for simulating soft tactile sensors.mp4 by Berith Atemoztli De la Cruz Sánchez (21758708)

    Published 2025
    “…A significant challenge for simulating tactile sensors is balancing the trade-off between accuracy and processing time in simulation algorithms and models. To address this, we propose a hybrid approach that combines elastic and hyperelastic finite element simulations, complemented by convolutional neural networks (CNNs), to generate synthetic tactile maps of a soft capacitive tactile sensor. …”
  10. 250

    Ablation study visualization results. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  11. 251

    Experimental parameter configuration. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  12. 252

    FLMP-YOLOv8 identification results. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  13. 253

    C2f structure. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  14. 254

    Experimental environment configuration. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  15. 255

    Ablation experiment results table. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  16. 256

    YOLOv8 identification results. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  17. 257

    LSKA module structure diagram. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  18. 258

    Comparison of mAP curves in ablation experiments. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  19. 259

    FarsterBlock structure. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”
  20. 260

    Sample augmentation and annotation illustration. by Xiaozhou Feng (2918222)

    Published 2025
    “…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …”