SMART GRID EMERGENCY POWER PROTECTION DATA ANALYSIS METHOD BASED ON AI ENGINE TECHNOLOGY. 1-14

Di Huang, Liangrong Xu, Bin Zhou, Chaoyue Zhu, Weiyan Zheng, and Xingping Yan

View Full Paper

References

  1. [1] Z. Su, Y. Wang, T. H. Luan, N. Zhang, F. Li, T. Chen, et al.,“Secure and efficient federated learning for smart grid with edge-cloud collaboration,” IEEE Transactions on Industrial Infor-matics, vol. 18, no. 2, pp. 1333–1344, 2021.
  2. [2] C. Chen, Y. Wu, J. Li, X. Wang, Z. Zeng, J. Xu, et al., “TBtools-II: A “one for all, all for one” bioinformatics platform for biologi-cal big-data mining,” Molecular Plant, vol. 16, no. 11, pp. 1733–1742, 2023.
  3. [3] Y. Wang, Z. Su, N. Zhang, J. Chen, X. Sun, Z. Ye, et al., “SPDS:A secure and auditable private data sharing scheme for smartgrid based on blockchain,” IEEE Transactions on IndustrialInformatics, vol. 17, no. 11, pp. 7688–7699, 2020.
  4. [4] T. Zhang, S. Dai, and Z. Cai, “Planning and fault control ofurban distribution lines through optimal design,” InternationalJournal of Power and Energy Systems, vol. 45, pp. 19–25, 2025.
  5. [5] R. Cai, B. Xia, X. Zhu, L. Wang, J. Gu, and J. Tang, “Designof a risk model and analytical decision information system forpower operation in the context of smart grid,” InternationalJournal of Power and Energy Systems, vol. 44, pp. 1–9, 2024.
  6. [6] X. Jia, Y. Zhang, G. Liu, X. Yang, T. Zhang, J. Zheng, et al.,“XVDPU: A high-performance CNN accelerator on the Versalplatform powered by the AI engine,” ACM Transactions on Re-configurable Technology and Systems, vol. 17, no. 2, pp. 1–24,2024.
  7. [7] H. Jupalle, S. Kouser, A. B. Bhatia, N. Alam, R. R. Nadikatt,and P. Whig, “Automation of human behaviors and its pre-diction using machine learning,” Microsystem Technologies,vol. 28, no. 8, pp. 1879–1887, 2022.
  8. [8] P. S. Thakur, T. Sheorey, and A. Ojha, “VGG-ICNN: Alightweight CNN model for crop disease identification,” Multi-media Tools and Applications, vol. 82, no. 1, pp. 497–520, 2023.
  9. [9] R. Akhter and S. A. Sofi, “Precision agriculture using IoTdata analytics and machine learning,” Journal of King SaudUniversity-Computer and Information Sciences, vol. 34, no. 8,pp. 5602–5618, 2022.
  10. [10] G. Wang, B. Zhao, B. Wu, C. Zhang, and W. Liu, “Intelligentprediction of slope stability based on visual exploratory dataanalysis of 77 in situ cases,” International Journal of MiningScience and Technology, vol. 33, no. 1, pp. 47–59, 2023.
  11. [11] S. Fosso Wamba, M. M. Queiroz, L. Wu, and U. Sivarajah,“Big data analytics-enabled sensing capability and organiza-tional outcomes,” Annals of Operations Research, vol. 333,no. 2, pp. 559–578, 2024.
  12. [12] S. Patil, N. DG, and A. Bhat, “Dynamic autoscaling andscheduling in Kubernetes clusters with LSTM and ILP,” Jour-nal of Communications Software and Systems, vol. 21, no. 4,pp. 465–476, 2025.
  13. [13] B. Magar, R. Kulkarni, V. Khatavkar, S. Parhad, and H. Van-jari, “Predictive network congestion management for enterprisesystems: a graph neural network approach,” Journal of Electri-cal Systems and Information Technology, vol. 12, no. 1, pp. 92–115, 2025.
  14. [14] S. K. Challa, A. Kumar, and V. B. Semwal, “A multibranchCNN-BiLSTM model for human activity recognition using wear-able sensor data,” The Visual Computer, vol. 38, no. 12,pp. 4095–4109, 2022.
  15. [15] S. Bag, S. Gupta, and L. Wood, “Big data analytics in sus-tainable humanitarian supply chain,” Annals of Operations Re-search, vol. 319, no. 1, pp. 721–760, 2022.
  16. [16] X. Zhao, P. Huang, and X. Shu, “Wavelet-attention CNN for im-age classification,” Multimedia Systems, vol. 28, no. 3, pp. 915–924, 2022.
  17. [17] U. Hewage, R. Sinha, and M. A. Naeem, “Privacy-preservingdata mining techniques and their impact on accuracy,” ArtificialIntelligence Review, vol. 56, no. 9, pp. 10427–10464, 2023.
  18. [18] S. M. Nengem, “Symmetric kernel-based approach for ellipticpartial differential equation,” Journal of Data Science and In-telligent Systems, vol. 1, no. 2, pp. 99–104, 2023.
  19. [19] C. Honrado, P. Bisegna, N. S. Swami, and F. Caselli, “Single-cell microfluidic impedance cytometry,” Lab on a Chip, vol. 21,no. 1, pp. 22–54, 2021.
  20. [20] E. Pairo-Castineira, S. Clohisey, L. Klaric, A. D. Bretherick,K. Rawlik, D. Pasko, et al., “Genetic mechanisms of criticalillness in COVID-19,” Nature, vol. 591, no. 7848, pp. 92–98,2021.
  21. [21] B. L. Neuen, M. Oshima, R. Agarwal, C. Arnott, D. Z. Cher-ney, R. Edwards, et al., “Sodium-glucose cotransporter 2 in-hibitors and risk of hyperkalemia,” Circulation, vol. 145, no. 19,pp. 1460–1470, 2022.
  22. [22] S. Lei, R. Zheng, S. Zhang, S. Wang, R. Chen, K. Sun, et al.,“Global patterns of breast cancer incidence and mortality,” Can-cer Communications, vol. 41, no. 11, pp. 1183–1194, 2021.

Important Links:

Go Back