These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
319 related articles for article (PubMed ID: 35804225)
1. Mid-long term forecasting of reservoir inflow using the coupling of time-varying filter-based empirical mode decomposition and gated recurrent unit. Wang X; Zhang S; Qiao H; Liu L; Tian F Environ Sci Pollut Res Int; 2022 Dec; 29(58):87200-87217. PubMed ID: 35804225 [TBL] [Abstract][Full Text] [Related]
2. A novel approach to precipitation prediction using a coupled CEEMDAN-GRU-Transformer model with permutation entropy algorithm. Zhao J; Nie G; Yan M; Wang Y; Wang L Water Sci Technol; 2023 Aug; 88(4):1015-1038. PubMed ID: 37651335 [TBL] [Abstract][Full Text] [Related]
3. Research on Deformation Prediction of VMD-GRU Deep Foundation Pit Based on PSO Optimization Parameters. Liu R; Zhang Q; Jiang F; Zhou J; He J; Mao Z Materials (Basel); 2024 May; 17(10):. PubMed ID: 38793264 [TBL] [Abstract][Full Text] [Related]
4. Monthly runoff prediction based on variational modal decomposition combined with the dung beetle optimization algorithm for gated recurrent unit model. Wen-Chao B; Liang-Duo S; Liang C; Chu-Tian X Environ Monit Assess; 2023 Nov; 195(12):1538. PubMed ID: 38012478 [TBL] [Abstract][Full Text] [Related]
5. Improving forecasting accuracy of medium and long-term runoff using artificial neural network based on EEMD decomposition. Wang WC; Chau KW; Qiu L; Chen YB Environ Res; 2015 May; 139():46-54. PubMed ID: 25684671 [TBL] [Abstract][Full Text] [Related]
6. A novel model for runoff prediction based on the ICEEMDAN-NGO-LSTM coupling. Yang C; Jiang Y; Liu Y; Liu S; Liu F Environ Sci Pollut Res Int; 2023 Jul; 30(34):82179-82188. PubMed ID: 37318729 [TBL] [Abstract][Full Text] [Related]
7. A hybrid prediction model of dissolved oxygen concentration based on secondary decomposition and bidirectional gate recurrent unit. Jiao J; Ma Q; Liu F; Zhao L; Huang S Environ Geochem Health; 2024 Mar; 46(4):127. PubMed ID: 38483668 [TBL] [Abstract][Full Text] [Related]
8. Using Complementary Ensemble Empirical Mode Decomposition and Gated Recurrent Unit to Predict Landslide Displacements in Dam Reservoir. Yang B; Xiao T; Wang L; Huang W Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214220 [TBL] [Abstract][Full Text] [Related]
9. A new strategy for groundwater level prediction using a hybrid deep learning model under Ecological Water Replenishment. Jia Z; Zhang Q; Shi B; Xu C; Liu D; Yang Y; Xi B; Li R Environ Sci Pollut Res Int; 2024 Apr; 31(16):23951-23967. PubMed ID: 38436858 [TBL] [Abstract][Full Text] [Related]
10. Improved prediction of chlorophyll-a concentrations in reservoirs by GRU neural network based on particle swarm algorithm optimized variational modal decomposition. Zhang X; Chen X; Zheng G; Cao G Environ Res; 2023 Mar; 221():115259. PubMed ID: 36634894 [TBL] [Abstract][Full Text] [Related]
11. A four-stage hybrid model for hydrological time series forecasting. Di C; Yang X; Wang X PLoS One; 2014; 9(8):e104663. PubMed ID: 25111782 [TBL] [Abstract][Full Text] [Related]
12. Analysis of the impact of the Xiaolangdi Reservoir on the runoff of the Yellow River downstream based on CEEMDAN-multiscale information entropy. Zhang X; Qiao W; Huang J; Shi J; Zhang M Water Sci Technol; 2023 Aug; 88(4):1058-1073. PubMed ID: 37651337 [TBL] [Abstract][Full Text] [Related]
13. CEGH: A Hybrid Model Using CEEMD, Entropy, GRU, and History Attention for Intraday Stock Market Forecasting. Liu Y; Liu X; Zhang Y; Li S Entropy (Basel); 2022 Dec; 25(1):. PubMed ID: 36673213 [TBL] [Abstract][Full Text] [Related]
14. A Novel Groundwater Burial Depth Prediction Model Based on Two-Stage Modal Decomposition and Deep Learning. Zhang X; Zheng Z Int J Environ Res Public Health; 2022 Dec; 20(1):. PubMed ID: 36612668 [TBL] [Abstract][Full Text] [Related]
15. Assessment of hybrid machine learning algorithms using TRMM rainfall data for daily inflow forecasting in TrĂªs Marias Reservoir, eastern Brazil. Gomaa E; Zerouali B; Difi S; El-Nagdy KA; Santos CAG; Abda Z; Ghoneim SSM; Bailek N; Silva RMD; Rajput J; Ali E Heliyon; 2023 Aug; 9(8):e18819. PubMed ID: 37593632 [TBL] [Abstract][Full Text] [Related]
16. Monthly-scale hydro-climatic forecasting and climate change impact evaluation based on a novel DCNN-Transformer network. Yang H; Zhang Z; Liu X; Jing P Environ Res; 2023 Nov; 236(Pt 2):116821. PubMed ID: 37541410 [TBL] [Abstract][Full Text] [Related]
17. Hybridized gated recurrent unit with variational mode decomposition and an error compensation mechanism for multi-step-ahead monthly rainfall forecasting. Wang D; Ren Y; Yang Y; Guo H Environ Sci Pollut Res Int; 2024 Jan; 31(1):1177-1194. PubMed ID: 38038925 [TBL] [Abstract][Full Text] [Related]
18. Noise Reduction Method of Underwater Acoustic Signals Based on Uniform Phase Empirical Mode Decomposition, Amplitude-Aware Permutation Entropy, and Pearson Correlation Coefficient. Li G; Yang Z; Yang H Entropy (Basel); 2018 Nov; 20(12):. PubMed ID: 33266642 [TBL] [Abstract][Full Text] [Related]
19. An improved framework to predict river flow time series data. Nazir HM; Hussain I; Ahmad I; Faisal M; Almanjahie IM PeerJ; 2019; 7():e7183. PubMed ID: 31304058 [TBL] [Abstract][Full Text] [Related]
20. Mid- and long-term runoff predictions by an improved phase-space reconstruction model. Hong M; Wang D; Wang Y; Zeng X; Ge S; Yan H; Singh VP Environ Res; 2016 Jul; 148():560-573. PubMed ID: 26632992 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]