Carbon Price Point–Interval Forecasting Based on Two-Layer Decomposition and Deep Learning Combined Model Using Weight Assignment DOI
Xiwen Cui, Dongxiao Niu

Journal of Cleaner Production, Год журнала: 2024, Номер unknown, С. 144124 - 144124

Опубликована: Окт. 1, 2024

Язык: Английский

MLP-Carbon: A new paradigm integrating multi-frequency and multi-scale techniques for accurate carbon price forecasting DOI
Zhirui Tian, Wei Sun, Chenye Wu

и другие.

Applied Energy, Год журнала: 2025, Номер 383, С. 125330 - 125330

Опубликована: Янв. 15, 2025

Язык: Английский

Процитировано

1
A novel probabilistic carbon price prediction model: Integrating the transformer framework with mixed-frequency modeling at different quartiles DOI

Mingyang Ji,

Jian Du, Pei Du

и другие.

Applied Energy, Год журнала: 2025, Номер 391, С. 125951 - 125951

Опубликована: Апрель 21, 2025

Язык: Английский

Процитировано

1
Incorporating key features from structured and unstructured data for enhanced carbon trading price forecasting with interpretability analysis DOI

Ming Jiang,

Jinxing Che, Shuying Li

и другие.

Applied Energy, Год журнала: 2025, Номер 382, С. 125301 - 125301

Опубликована: Янв. 8, 2025

Язык: Английский

Процитировано

0
Forecasting carbon price in Hubei Province using a mixed neural model based on mutual information and Multi-head Self-Attention DOI
Youyang Ren, Yuan-zhong Huang, Yuhong Wang

и другие.

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 144960 - 144960

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
From forecasting to trading: A multimodal-data-driven approach to reversing carbon market losses DOI

Shuihan Liu,

Mingchen Li, Kun Yang

и другие.

Energy Economics, Год журнала: 2025, Номер 144, С. 108350 - 108350

Опубликована: Фев. 28, 2025

Язык: Английский

Процитировано

0
China’s Energy Stock Price Index Prediction Based on VECM–BiLSTM Model DOI Creative Commons
Bingchun Liu, Zhang Xia, Yuan Gao

и другие.

Energies, Год журнала: 2025, Номер 18(5), С. 1242 - 1242

Опубликована: Март 3, 2025

The energy stock price index maps the development trends in China’s market to a certain extent, and accurate forecasting of can effectively guide government regulate policies cope with external risks. vector error correction model (VECM) analyzes relationship between each indicator output, provides an explanation for way influences output indicator, uses this filter input indicators. forecast results China 2022–2024 showed upward trend, evaluation parameters MAE, MAPE, RMSE were 0.2422, 3.5704% 0.3529, respectively, higher efficiency than other comparative models. Finally, impact different indicators on Chinese was analyzed through scenario setting. show that oscillations real commodity factor (RCPF) global economic conditions (GECON) cause fluctuations indices evolves same manner as changes two international indices: MSCI World Index FTSE 100 Index.

Язык: Английский

Процитировано

0
Field measurement and CFD simulation study on UHI in high-density blocks of Shanghai based on street canyons DOI
Deng Ying, Xiangfei Kong,

Haizhu Zhou

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106302 - 106302

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
A Novel Forecasting Framework for Carbon Emission Trading Price Based on Nonlinear Integration DOI Creative Commons

R. Gao,

Jingyun Sun

Mathematics, Год журнала: 2025, Номер 13(10), С. 1624 - 1624

Опубликована: Май 15, 2025

The complex features of carbon price, such as volatility and nonlinearity, pose a serious challenge to accurately predict it. To this end, paper proposes novel forecasting framework for emission trading price based on nonlinear integration, including feature selection, deep learning model combination. Firstly, the historical series are collected collated, factors affecting analyzed. Secondly, data downscaled input variables screened using max-relevance min-redundancy. Then, three integrated models combined with neural network through integration construct hybrid prediction model, best performing is obtained. Finally, interval realized basis point prediction. experimental results show that outperforms other comparative in terms accuracy, stability statistical hypothesis testing, has good performance. In summary, proposed can not only provide high-precision market government enterprise decision makers, but also help investors optimize their strategies improve returns.

Язык: Английский

Процитировано

0
Carbon price prediction based on multidimensional association rules and optimized multi-factor LSTM model DOI
Xinqi Tu, Lianlian Fu, Lingling Wang

и другие.

Energy, Год журнала: 2025, Номер unknown, С. 136768 - 136768

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0
A novel carbon price forecasting model integrating mixed-frequency modeling into the transformer architecture from a multi-factor perspective DOI

Mingyang Ji,

Juntao Du, Pei Du

и другие.

Expert Systems with Applications, Год журнала: 2025, Номер 289, С. 128300 - 128300

Опубликована: Май 30, 2025

Язык: Английский

Процитировано

0