Open Access
| Issue |
E3S Web of Conf.
Volume 405, 2023
2023 International Conference on Sustainable Technologies in Civil and Environmental Engineering (ICSTCE 2023)
|
|
|---|---|---|
| Article Number | 04003 | |
| Number of page(s) | 9 | |
| Section | Sustainable Technologies in Construction & Environmental Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202340504003 | |
| Published online | 26 July 2023 | |
- Dechao Sun, Jiali Wu, Hong Huang, Renfang Wang, Feng Liang, Hong Xinhua, “Prediction of Short-Time Rainfall Based on Deep Learning”, Mathematical Problems in Engineering, vol. 2021, Article ID 6664413, 8 pages (2021). [Google Scholar]
- Yash Gaur, Anika Jain, Georgios Sarmonikas “Precipitation Nowcasting using Deep Learning Techniques”CS230: Deep Learning, Winter 2020, Stanford University, CA (2020) [Google Scholar]
- Georgy Ayzel, Tobias Scheffer, Maik Heistermann “A Convolutional neural network for radar-based precipitation nowcasting”, Procedia Computer Science (2020) [Google Scholar]
- Tuyen DN, Tuan TM, Le X-H, Tung NT, Chau TK, Van Hai P, Gerogiannis VC, Son LH “Rain Pred RNN: A New Approach for Precipitation Nowcasting with Weather Radar Echo Images Based on Deep Learning” Axioms.11(3):107. https://doi.org/10.3390/axioms11030107(2020) [Google Scholar]
- Kevin Trebing, Tomasz Stanczyk, Siamak Mehrkanoon, “SmaAt-UNet: Precipitation Nowcasting using a Small Attention-UNet Architecture”, Axioms (2020) [Google Scholar]
- Shreya Agrawal et al. “Machine Learning for Precipitation Nowcasting from Radar Images”. In: arXiv: 1912.12132 [cs.CV] (2019) [Google Scholar]
- Yunbo wang, Mingsheng long, jijamin wang “Pred RNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs”, Advances in neural information processing systems (2017) [Google Scholar]
- Wang-chun WOO and Wai Kin Wong. “Operational Application of Optical Flow Techniques to Radar-Based Rainfall Nowcasting”. In: Atmosphere, p. 48. DOI: 10.3390/ atmos8030048 (2017) [Google Scholar]
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