135 related articles for article (PubMed ID: 35982382)
1. China's carbon dioxide emission forecast based on improved marine predator algorithm and multi-kernel support vector regression.
Qin X; Zhang S; Dong X; Zhan Y; Wang R; Xu D
Environ Sci Pollut Res Int; 2023 Jan; 30(3):5730-5748. PubMed ID: 35982382
[TBL] [Abstract][Full Text] [Related]
2. Modelling and forecasting non-renewable energy consumption and carbon dioxide emissions in China using a PSO algorithm-based fractional non-linear grey Bernoulli model.
Yang J; Wu Z
Environ Sci Pollut Res Int; 2023 Jun; 30(26):69651-69665. PubMed ID: 37142841
[TBL] [Abstract][Full Text] [Related]
3. Reduced carbon emission estimates from fossil fuel combustion and cement production in China.
Liu Z; Guan D; Wei W; Davis SJ; Ciais P; Bai J; Peng S; Zhang Q; Hubacek K; Marland G; Andres RJ; Crawford-Brown D; Lin J; Zhao H; Hong C; Boden TA; Feng K; Peters GP; Xi F; Liu J; Li Y; Zhao Y; Zeng N; He K
Nature; 2015 Aug; 524(7565):335-8. PubMed ID: 26289204
[TBL] [Abstract][Full Text] [Related]
4. Analysis influence factors and forecast energy-related CO
Sun W; Zhang J
Environ Monit Assess; 2020 Oct; 192(10):665. PubMed ID: 33001326
[TBL] [Abstract][Full Text] [Related]
5. Determinants investigation and peak prediction of CO
Wang W; Wang J
Environ Sci Pollut Res Int; 2021 Oct; 28(39):55535-55553. PubMed ID: 34138431
[TBL] [Abstract][Full Text] [Related]
6. Drivers of the peaking and decoupling between CO
Gong W; Wang C; Fan Z; Xu Y
Environ Sci Pollut Res Int; 2022 Jan; 29(3):3864-3878. PubMed ID: 34398378
[TBL] [Abstract][Full Text] [Related]
7. A comparative study of statistical and machine learning models on carbon dioxide emissions prediction of China.
Li X; Zhang X
Environ Sci Pollut Res Int; 2023 Nov; 30(55):117485-117502. PubMed ID: 37867169
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Simulation analysis of carbon peak path in China from a multi-scenario perspective: evidence from random forest and back propagation neural network models.
Li Y; Huang S; Miao L; Wu Z
Environ Sci Pollut Res Int; 2023 Apr; 30(16):46711-46726. PubMed ID: 36723842
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Predicting carbon dioxide emissions in the United States of America using machine learning algorithms.
Chukwunonso BP; Al-Wesabi I; Shixiang L; AlSharabi K; Al-Shamma'a AA; Farh HMH; Saeed F; Kandil T; Al-Shaalan AM
Environ Sci Pollut Res Int; 2024 May; 31(23):33685-33707. PubMed ID: 38691282
[TBL] [Abstract][Full Text] [Related]
12. Assessing the possibility of China reaching carbon emission peak by 2030 in the context of the COVID-19 pandemic.
Chen T; Ren Y; Yang J; Cong G
Environ Sci Pollut Res Int; 2023 Nov; 30(52):111995-112018. PubMed ID: 37824049
[TBL] [Abstract][Full Text] [Related]
13. Assessing the contribution of optimizing energy mix to China's carbon peaking.
Wang F; Han H; Liu L; Zhao J
Environ Sci Pollut Res Int; 2023 Feb; 30(7):18296-18311. PubMed ID: 36208379
[TBL] [Abstract][Full Text] [Related]
14. Modeling and Estimation of CO
Wang P; Zhong Y; Yao Z
Comput Intell Neurosci; 2022; 2022():6822467. PubMed ID: 35845901
[TBL] [Abstract][Full Text] [Related]
15. A novel grey Verhulst model with four parameters and its application to forecast the carbon dioxide emissions in China.
Zeng B; Zheng T; Yang Y; Wang J
Sci Total Environ; 2023 Nov; 899():165648. PubMed ID: 37482363
[TBL] [Abstract][Full Text] [Related]
16. Forecast of China's carbon emissions under the background of carbon neutrality.
Shi M
Environ Sci Pollut Res Int; 2022 Jun; 29(28):43019-43033. PubMed ID: 35091929
[TBL] [Abstract][Full Text] [Related]
17. Analysis of influencing factors of the carbon dioxide emissions in China's commercial department based on the STIRPAT model and ridge regression.
Wen L; Shao H
Environ Sci Pollut Res Int; 2019 Sep; 26(26):27138-27147. PubMed ID: 31321715
[TBL] [Abstract][Full Text] [Related]
18. Decomposition of drivers and identification of decoupling states for the evolution of carbon emissions from energy consumption in China.
Wang Y; Mo S; Zhang C; Zhi J; Li C
Environ Sci Pollut Res Int; 2023 Jun; 30(30):75629-75654. PubMed ID: 37222887
[TBL] [Abstract][Full Text] [Related]
19. Research on the Duality of China's Marine Fishery Carbon Emissions and Its Coordination with Economic Development.
Xiong H; Wang X; Hu X
Int J Environ Res Public Health; 2023 Jan; 20(2):. PubMed ID: 36674174
[TBL] [Abstract][Full Text] [Related]
20. Forecasting CO
Wei S; Yuwei W; Chongchong Z
Environ Sci Pollut Res Int; 2018 Oct; 25(29):28985-28997. PubMed ID: 30109681
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]