168 related articles for article (PubMed ID: 33983991)
1. Prediction of direct carbon emissions of Chinese provinces using artificial neural networks.
Jin H
PLoS One; 2021; 16(5):e0236685. PubMed ID: 33983991
[TBL] [Abstract][Full Text] [Related]
2. Analysis and prediction of the temporal and spatial evolution of carbon emissions in China's eight economic regions.
Yu Z; Zhang Y; Zhang J; Zhang W
PLoS One; 2022; 17(12):e0277906. PubMed ID: 36454795
[TBL] [Abstract][Full Text] [Related]
3. Carbon peaking prediction scenarios based on different neural network models: A case study of Guizhou Province.
Lian D; Yang SQ; Yang W; Zhang M; Ran WR
PLoS One; 2024; 19(6):e0296596. PubMed ID: 38917224
[TBL] [Abstract][Full Text] [Related]
4. Carbon emissions predicting and decoupling analysis based on the PSO-ELM combined prediction model: evidence from Chongqing Municipality, China.
Liu B; Chang H; Li Y; Zhao Y
Environ Sci Pollut Res Int; 2023 Jul; 30(32):78849-78864. PubMed ID: 37280494
[TBL] [Abstract][Full Text] [Related]
5. Application of grey model in influencing factors analysis and trend prediction of carbon emission in Shanxi Province.
Wang M; Wu L; Guo X
Environ Monit Assess; 2022 Jun; 194(8):542. PubMed ID: 35771294
[TBL] [Abstract][Full Text] [Related]
6. Prediction of CO2 emissions in China by generalized regression neural network optimized with fruit fly optimization algorithm.
Yue H; Bu L
Environ Sci Pollut Res Int; 2023 Jul; 30(33):80676-80692. PubMed ID: 37301812
[TBL] [Abstract][Full Text] [Related]
7. The Evolution of the Spatial Association Effect of Carbon Emissions in Transportation: A Social Network Perspective.
Ma F; Wang Y; Yuen KF; Wang W; Li X; Liang Y
Int J Environ Res Public Health; 2019 Jun; 16(12):. PubMed ID: 31216689
[TBL] [Abstract][Full Text] [Related]
8. Investigation of a spatial coupling relationship between carbon emission performance and regional urbanization in China.
Zhou H; Wang P; Wang C; Deng X; Liu K
PLoS One; 2019; 14(9):e0222534. PubMed ID: 31568514
[TBL] [Abstract][Full Text] [Related]
9. Research Progress and Hotspot Analysis of Residential Carbon Emissions Based on CiteSpace Software.
Chen Y; Chen Y; Chen K; Liu M
Int J Environ Res Public Health; 2023 Jan; 20(3):. PubMed ID: 36767072
[TBL] [Abstract][Full Text] [Related]
10. Coupling and decoupling effects of agricultural carbon emissions in China and their driving factors.
Han H; Zhong Z; Guo Y; Xi F; Liu S
Environ Sci Pollut Res Int; 2018 Sep; 25(25):25280-25293. PubMed ID: 29946837
[TBL] [Abstract][Full Text] [Related]
11. Research on the potential for China to achieve carbon neutrality: A hybrid prediction model integrated with elman neural network and sparrow search algorithm.
Yang M; Liu Y
J Environ Manage; 2023 Mar; 329():117081. PubMed ID: 36549053
[TBL] [Abstract][Full Text] [Related]
12. A new multiregional carbon emissions forecasting model based on a multivariable information fusion mechanism and hybrid spatiotemporal graph convolution network.
Shao Z; Gao S; Zhou K; Yang S
J Environ Manage; 2024 Feb; 352():119976. PubMed ID: 38198835
[TBL] [Abstract][Full Text] [Related]
13. Construction of Game Model between Carbon Emission Minimization and Energy and Resource Economy Maximization Based on Deep Neural Network.
Ma L; Wang D
Comput Intell Neurosci; 2022; 2022():4578536. PubMed ID: 35548100
[TBL] [Abstract][Full Text] [Related]
14. Factors influencing carbon dioxide emissions in Iran's provinces with emphasis on spatial linkages.
Mamipour S; Beheshtipour H; Feshari M; Amiri H
Environ Sci Pollut Res Int; 2019 Jun; 26(18):18365-18378. PubMed ID: 31041715
[TBL] [Abstract][Full Text] [Related]
15. A novel grey prediction model with a feedforward neural network based on a carbon emission dynamic evolution system and its application.
Nie W; Ao O; Duan H
Environ Sci Pollut Res Int; 2023 Feb; 30(8):20704-20720. PubMed ID: 36253576
[TBL] [Abstract][Full Text] [Related]
16. Forecasting the annual household electricity consumption of Chinese residents using the DPSO-BP prediction model.
Wen L; Yuan X
Environ Sci Pollut Res Int; 2020 Jun; 27(17):22014-22032. PubMed ID: 32291639
[TBL] [Abstract][Full Text] [Related]
17. The spatial characteristics of embodied carbon emission flow in Chinese provinces: a network-based perspective.
Song J; Hu X; Wang X; Yuan W; Wang T
Environ Sci Pollut Res Int; 2022 May; 29(23):34955-34973. PubMed ID: 35043298
[TBL] [Abstract][Full Text] [Related]
18. Short-term prediction of carbon emissions based on the EEMD-PSOBP model.
Sun W; Ren C
Environ Sci Pollut Res Int; 2021 Oct; 28(40):56580-56594. PubMed ID: 34060019
[TBL] [Abstract][Full Text] [Related]
19. Forecasting carbon emissions from energy consumption in Guangdong Province, China with a novel grey multivariate model.
Wan G; Li X; Yin K; Zhao Y
Environ Sci Pollut Res Int; 2022 Aug; 29(39):59534-59546. PubMed ID: 35386078
[TBL] [Abstract][Full Text] [Related]
20. Energy carbon emission structure and reduction potential focused on the supply-side and demand-side.
Kang J; Yang Y
PLoS One; 2020; 15(10):e0239634. PubMed ID: 33021990
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
