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.
143 related articles for article (PubMed ID: 38321281)
21. Ensemble streamflow forecasting based on variational mode decomposition and long short term memory. Sun X; Zhang H; Wang J; Shi C; Hua D; Li J Sci Rep; 2022 Jan; 12(1):518. PubMed ID: 35017569 [TBL] [Abstract][Full Text] [Related]
22. Carbon price forecasting based on modified ensemble empirical mode decomposition and long short-term memory optimized by improved whale optimization algorithm. Yang S; Chen D; Li S; Wang W Sci Total Environ; 2020 May; 716():137117. PubMed ID: 32074939 [TBL] [Abstract][Full Text] [Related]
23. Multi-step-ahead and interval carbon price forecasting using transformer-based hybrid model. Yue W; Zhong W; Xiaoyi W; Xinyu K Environ Sci Pollut Res Int; 2023 Sep; 30(42):95692-95719. PubMed ID: 37558913 [TBL] [Abstract][Full Text] [Related]
24. A hybrid forecasting approach for China's national carbon emission allowance prices with balanced accuracy and interpretability. Mao Y; Yu X J Environ Manage; 2024 Feb; 351():119873. PubMed ID: 38159311 [TBL] [Abstract][Full Text] [Related]
25. Short-term power load forecasting in China: A Bi-SATCN neural network model based on VMD-SE. Huang Y; Feng Q; Han F PLoS One; 2024; 19(9):e0311194. PubMed ID: 39348423 [TBL] [Abstract][Full Text] [Related]
26. A two-stage interval-valued carbon price forecasting model based on bivariate empirical mode decomposition and error correction. Wang P; Chudhery MAZ; Xu J; Zhao X; Wang C Environ Sci Pollut Res Int; 2023 Jul; 30(32):78262-78278. PubMed ID: 37269510 [TBL] [Abstract][Full Text] [Related]
27. A novel short-term carbon emission prediction model based on secondary decomposition method and long short-term memory network. Kong F; Song J; Yang Z Environ Sci Pollut Res Int; 2022 Sep; 29(43):64983-64998. PubMed ID: 35482236 [TBL] [Abstract][Full Text] [Related]
28. A hybrid air quality early-warning framework: An hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms. Sharma E; Deo RC; Prasad R; Parisi AV Sci Total Environ; 2020 Mar; 709():135934. PubMed ID: 31869708 [TBL] [Abstract][Full Text] [Related]
29. Water quality assessment of a river using deep learning Bi-LSTM methodology: forecasting and validation. Khullar S; Singh N Environ Sci Pollut Res Int; 2022 Feb; 29(9):12875-12889. PubMed ID: 33988840 [TBL] [Abstract][Full Text] [Related]
30. An ensemble LSTM-based AQI forecasting model with decomposition-reconstruction technique via CEEMDAN and fuzzy entropy. Wu Z; Zhao W; Lv Y Air Qual Atmos Health; 2022; 15(12):2299-2311. PubMed ID: 36196368 [TBL] [Abstract][Full Text] [Related]
31. Short-term wind speed forecasting based on a hybrid model of ICEEMDAN, MFE, LSTM and informer. Xinxin W; Xiaopan S; Xueyi A; Shijia L PLoS One; 2023; 18(9):e0289161. PubMed ID: 37682883 [TBL] [Abstract][Full Text] [Related]
32. Modeling opening price spread of Shanghai Composite Index based on ARIMA-GRU/LSTM hybrid model. Si Y; Nadarajah S; Zhang Z; Xu C PLoS One; 2024; 19(3):e0299164. PubMed ID: 38478502 [TBL] [Abstract][Full Text] [Related]
33. A new hybrid prediction model of PM Yang H; Zhao J; Li G Environ Sci Pollut Res Int; 2022 Sep; 29(44):67214-67241. PubMed ID: 35524096 [TBL] [Abstract][Full Text] [Related]
34. Predicting the monthly consumption and production of natural gas in the USA by using a new hybrid forecasting model based on two-layer decomposition. Jiang S; Zhao XT; Li N Environ Sci Pollut Res Int; 2023 Mar; 30(14):40799-40824. PubMed ID: 36622613 [TBL] [Abstract][Full Text] [Related]
35. A new hybrid prediction model of air quality index based on secondary decomposition and improved kernel extreme learning machine. Li G; Tang Y; Yang H Chemosphere; 2022 Oct; 305():135348. PubMed ID: 35718028 [TBL] [Abstract][Full Text] [Related]
36. An Economic Forecasting Method Based on the LightGBM-Optimized LSTM and Time-Series Model. Lv J; Wang C; Gao W; Zhao Q Comput Intell Neurosci; 2021; 2021():8128879. PubMed ID: 34621309 [TBL] [Abstract][Full Text] [Related]
37. An optimized decomposition integration framework for carbon price prediction based on multi-factor two-stage feature dimension reduction. Xu W; Wang J; Zhang Y; Li J; Wei L Ann Oper Res; 2022 Jul; ():1-38. PubMed ID: 35875369 [TBL] [Abstract][Full Text] [Related]
38. 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]
39. Characteristic mango price forecasting using combined deep-learning optimization model. Ma X; Tong J; Huang W; Lin H PLoS One; 2023; 18(4):e0283584. PubMed ID: 37053221 [TBL] [Abstract][Full Text] [Related]
40. An adaptive particle swarm optimization-based hybrid long short-term memory model for stock price time series forecasting. Kumar G; Singh UP; Jain S Soft comput; 2022; 26(22):12115-12135. PubMed ID: 36043118 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]