Search alternatives:
grid research » pain research (Expand Search)
Showing 541 - 560 results of 1,613 for search 'Grid research algorithm', query time: 0.13s Refine Results
  1. 541
  2. 542
  3. 543

    Assessing the risk of traffic accidents in lisbon using a gradient boosting algorithm with a hybrid classification/regression approach by Nuno Alpalhão, Pedro Sarmento, Bruno Jardim, Miguel de Castro Neto

    Published 2025-07-01
    “…This research presents a novel two-stage gradient-boosting predictive model, using tree-based learning algorithms to analyze traffic accidents requiring firefighter intervention in Lisbon, Portugal. …”
    Get full text
    Article
  4. 544
  5. 545
  6. 546
  7. 547

    Penerapan Feature Engineering dan Hyperparameter Tuning untuk Meningkatkan Akurasi Model Random Forest pada Klasifikasi Risiko Kredit by Nadea Putri Nur Fauzi, Siti Khomsah, Aditya Dwi Putra Wicaksono

    Published 2025-04-01
    “…This research aims to improve the accuracy of the Random Forest algorithm classification model by implementing parameter tuning and feature engineering. …”
    Get full text
    Article
  8. 548
  9. 549
  10. 550
  11. 551
  12. 552
  13. 553

    Rendering algorithm for 3D model of goods in power warehouse based on linear interpolation and 2D texture mapping by Gui Luo, Xin Chen, Quan Liu, Anlin Liu, Xuan Zhang, Li Tian, Yueshi Gao

    Published 2025-08-01
    “…Deployment at a State Grid hub warehouse elevated sorting throughput by 40% and slashed manual verification workload by 65%. …”
    Get full text
    Article
  14. 554
  15. 555

    Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data by Shaohui Zhou, Zhiqiu Gao, Bo Gong, Hourong Zhang, Haipeng Zhang, Jinqiang He, Xingya Xi

    Published 2025-06-01
    “…In this study, we propose a new approach for constructing real-time icing grid fields using 1339 online terminal monitoring datasets provided by the China Southern Power Grid Research Institute Co., Ltd. …”
    Get full text
    Article
  16. 556
  17. 557
  18. 558
  19. 559

    Solar FaultNet: Advanced Fault Detection and Classification in Solar PV Systems Using SwinProba‐GeNet and BaBa Optimizer Models by Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri, Faisal Alsaif

    Published 2025-07-01
    “…Besides, the proposed model outperforms conventional machine‐learning algorithms and state‐of‐the‐art deep‐ learning models for better performance by yielding higher accuracy, precision, recall, F1‐score, and low error rate on various fault types such as PV array faults, inverter faults, grid synchronization faults, and environmental faults. …”
    Get full text
    Article
  20. 560