SEED: An Effective Model for Highly-Skewed Streamflow Time Series Data Forecasting

Yanhong Li, Jack Xu, David C. Anastasiu. SEED: An Effective Model for Highly-Skewed Streamflow Time Series Data Forecasting. In Jingrui He, Themis Palpanas, Xiaohua Hu, Alfredo Cuzzocrea, Dejing Dou, Dominik Slezak, Wei Wang, Aleksandra Gruca, Jerry Chun-Wei Lin, Rakesh Agrawal 0001, editors, IEEE International Conference on Big Data, BigData 2023, Sorrento, Italy, December 15-18, 2023. pages 728-737, IEEE, 2023. [doi]

@inproceedings{LiXA23-0,
  title = {SEED: An Effective Model for Highly-Skewed Streamflow Time Series Data Forecasting},
  author = {Yanhong Li and Jack Xu and David C. Anastasiu},
  year = {2023},
  doi = {10.1109/BigData59044.2023.10386959},
  url = {https://doi.org/10.1109/BigData59044.2023.10386959},
  researchr = {https://researchr.org/publication/LiXA23-0},
  cites = {0},
  citedby = {0},
  pages = {728-737},
  booktitle = {IEEE International Conference on Big Data, BigData 2023, Sorrento, Italy, December 15-18, 2023},
  editor = {Jingrui He and Themis Palpanas and Xiaohua Hu and Alfredo Cuzzocrea and Dejing Dou and Dominik Slezak and Wei Wang and Aleksandra Gruca and Jerry Chun-Wei Lin and Rakesh Agrawal 0001},
  publisher = {IEEE},
  isbn = {979-8-3503-2445-7},
}