177 related articles for article (PubMed ID: 38085727)
1. Predicting regional carbon price in China based on multi-factor HKELM by combining secondary decomposition and ensemble learning.
Hu B; Cheng Y
PLoS One; 2023; 18(12):e0285311. PubMed ID: 38085727
[TBL] [Abstract][Full Text] [Related]
2. Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm.
Yun P; Zhou Y; Liu C; Wu Y; Pan D
Environ Sci Pollut Res Int; 2024 Mar; 31(11):16530-16553. PubMed ID: 38321281
[TBL] [Abstract][Full Text] [Related]
3. A carbon price hybrid forecasting model based on data multi-scale decomposition and machine learning.
Yang P; Wang Y; Zhao S; Chen Z; Li Y
Environ Sci Pollut Res Int; 2023 Jan; 30(2):3252-3269. PubMed ID: 35943654
[TBL] [Abstract][Full Text] [Related]
4. Carbon price prediction using multiple hybrid machine learning models optimized by genetic algorithm.
Nadirgil O
J Environ Manage; 2023 Sep; 342():118061. PubMed ID: 37201388
[TBL] [Abstract][Full Text] [Related]
5. Carbon price prediction based on multiple decomposition and XGBoost algorithm.
Xu K; Xia Z; Cheng M; Tan X
Environ Sci Pollut Res Int; 2023 Aug; 30(38):89165-89179. PubMed ID: 37442936
[TBL] [Abstract][Full Text] [Related]
6. A novel hybrid model based on two-stage data processing and machine learning for forecasting chlorophyll-a concentration in reservoirs.
Yu W; Wang X; Jiang X; Zhao R; Zhao S
Environ Sci Pollut Res Int; 2024 Jan; 31(1):262-279. PubMed ID: 38015396
[TBL] [Abstract][Full Text] [Related]
7. Predicting carbon futures prices based on a new hybrid machine learning: Comparative study of carbon prices in different periods.
Zhang X; Yang K; Lu Q; Wu J; Yu L; Lin Y
J Environ Manage; 2023 Nov; 346():118962. PubMed ID: 37714085
[TBL] [Abstract][Full Text] [Related]
8. Forecasting carbon futures price: a hybrid method incorporating fuzzy entropy and extreme learning machine.
Chen P; Vivian A; Ye C
Ann Oper Res; 2022; 313(1):559-601. PubMed ID: 35002000
[TBL] [Abstract][Full Text] [Related]
9. A novel carbon price forecasting method based on model matching, adaptive decomposition, and reinforcement learning ensemble strategy.
Cao Z; Liu H
Environ Sci Pollut Res Int; 2023 Mar; 30(13):36044-36067. PubMed ID: 36539662
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Carbon price prediction for China's ETS pilots using variational mode decomposition and optimized extreme learning machine.
Chai S; Zhang Z; Zhang Z
Ann Oper Res; 2021 Nov; ():1-22. PubMed ID: 34812214
[TBL] [Abstract][Full Text] [Related]
12. Research on a Novel Hybrid Decomposition-Ensemble Learning Paradigm Based on VMD and IWOA for PM
Guo H; Guo Y; Zhang W; He X; Qu Z
Int J Environ Res Public Health; 2021 Jan; 18(3):. PubMed ID: 33498934
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition.
Zhang X; Zhang Q; Zhang G; Nie Z; Gui Z; Que H
Int J Environ Res Public Health; 2018 May; 15(5):. PubMed ID: 29883381
[TBL] [Abstract][Full Text] [Related]
15. Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks.
Huang Z; Zhang W
J Environ Manage; 2024 May; 359():120967. PubMed ID: 38723494
[TBL] [Abstract][Full Text] [Related]
16. Breaking through the limitation of carbon price forecasting: A novel hybrid model based on secondary decomposition and nonlinear integration.
Lan Y; Huangfu Y; Huang Z; Zhang C
J Environ Manage; 2024 Jun; 362():121253. PubMed ID: 38823294
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. 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]
19. 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]
20. A novel hybrid learning paradigm with feature extraction for carbon price prediction based on Bi-directional long short-term memory network optimized by an improved sparrow search algorithm.
Zhou J; Xu Z; Wang S
Environ Sci Pollut Res Int; 2022 Sep; 29(43):65585-65598. PubMed ID: 35488159
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
