Open Access
| Issue |
E3S Web Conf.
Volume 228, 2021
2020 International Conference on Climate Change, Green Energy and Environmental Sustainability (CCGEES 2020)
|
|
|---|---|---|
| Article Number | 02014 | |
| Number of page(s) | 5 | |
| Section | Climate Change and Environmental Ecological Sustainable Development Analysis | |
| DOI | https://doi.org/10.1051/e3sconf/202122802014 | |
| Published online | 13 January 2021 | |
- Sehgal V, Tiwari M K, Chatterjee C. Wavelet bootstrap multiple line-ar regression based hybrid modeling for daily river discharge forecas-Ting [J]. Water Resources Management, (2014, 28 (10):2793-2811). [CrossRef] [Google Scholar]
- Guo Qingchun, He Zhenfang, Li Li, Li Haining. Application of BP artificial neural network Model in water pollution index prediction of Taihu Lake [J]. Journal of southern agriculture, (2011), 42(10):1303-1306). [Google Scholar]
- Li Yinghui. Research on water pollution Prediction and Treatment Countermeasures of the Three Gorges Reservoir Area based on grey system Model [J]. Journal of chongqing university of technology (social sciences), (2020), 34(03):46-55). [Google Scholar]
- Yu Ting Zhan, Li Yong, Bai Yun, Li Chuan. Research Status of Water pollution Prediction Methods [J]. Green Science and Technology, 2017(14):53-55+58). [Google Scholar]
- Wang Siwen, Qi Shaoqun, Yu Dandan, Zhang Yuwei, Wan Luhe. Research on Water Environment Quality Prediction and Evaluation based on WASP Model -A Case study of Halbinjiang Section of Songhua River [J]. Journal of natural disasters, (2015, 24(01):39-45). [Google Scholar]
- Chen Yue, Xi Beidou, He Liansheng, Wang Jinggang. Application of QUAL2K Model in water Quality Simulation of Meixi Section of Xitiao-Xi Trunk Stream [J]. Journal of Environmental Engineering, (2008(07):1000-1003). [Google Scholar]
- Jiang Baiquan. Application of artificial neural network in water environment quality evaluation and prediction [D]. Capital Normal University, 2007. [Google Scholar]
- Liu Kun, Liu Xianzhao, Sun Jin, Meng Cuiling. Comprehensive Evaluation of Water Environment Quality based on Support Vector Machine [J]. China Environmental Monitoring, (2007(03):81-84). [Google Scholar]
- Zhang Xiuju, An Huan, Zhao Wenrong, Zhang Qinling. Examples of Water Quality prediction based on Support vector Machine [J]. China Rural Water Conservancy and Hydropower, (2015(01):85-89). [Google Scholar]
- Yu Ting Zhan, Li Yong, Bai Yun, Li Chuan. Research Status of Water pollution Prediction Methods [J]. Green Science and Technology(, 2017(14):53-55+58). [Google Scholar]
- Vapmk V. The essence of statistical learning theory. Zhang Xue-gong translation. Beijing: Tsinghua University Press, 20 [Google Scholar]
- Zhang Sen. Research on Water Quality Evaluation and Prediction based on Partial Least squares support Vector Machine [D]. Chongqing University, (2014). [Google Scholar]
- Liu Jing-xu. Model Selection and Application of Support vector Regression [D]. National University of Defense Science and technology, (2006). [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.