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Carbon price forecasting based on CEEMDAN and LSTM

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  1. Li, Dan & Li, Yijun & Wang, Chaoqun & Chen, Min & Wu, Qi, 2023. "Forecasting carbon prices based on real-time decomposition and causal temporal convolutional networks," Applied Energy, Elsevier, vol. 331(C).
  2. Zhang, Dongdong & Chen, Baian & Zhu, Hongyu & Goh, Hui Hwang & Dong, Yunxuan & Wu, Thomas, 2023. "Short-term wind power prediction based on two-layer decomposition and BiTCN-BiLSTM-attention model," Energy, Elsevier, vol. 285(C).
  3. Tang, Xianlun & Xia, Yu & Jiang, Lin & Xiong, Deyi & Wang, Lejun & Wang, Ying, 2025. "Dynamic adaptive hierarchical TCN driven by IHOA-VMD optimization for short term load forecasting," Energy, Elsevier, vol. 335(C).
  4. Jiang, Meiqin & Che, Jinxing & Li, Shuying & Hu, Kun & Xu, Yifan, 2025. "Incorporating key features from structured and unstructured data for enhanced carbon trading price forecasting with interpretability analysis," Applied Energy, Elsevier, vol. 382(C).
  5. Ting Yao & Charbel Salloum & Yong Jiang & Yi‐Shuai Ren, 2026. "Can Attention Mechanisms Improve Carbon Price Forecasting Accuracy?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(1), pages 156-178, January.
  6. Xiong, Xiaoping & Qing, Guohua, 2023. "A hybrid day-ahead electricity price forecasting framework based on time series," Energy, Elsevier, vol. 264(C).
  7. Ding, Lili & Zhang, Rui & Zhao, Xin, 2024. "Forecasting carbon price in China unified carbon market using a novel hybrid method with three-stage algorithm and long short-term memory neural networks," Energy, Elsevier, vol. 288(C).
  8. Yin, Linfei & Qiu, Yao, 2022. "Neural network dynamic differential control for long-term price guidance mechanism of flexible energy service providers," Energy, Elsevier, vol. 255(C).
  9. Qin, Chaoyong & Qin, Dongling & Jiang, Qiuxian & Zhu, Bangzhu, 2024. "Forecasting carbon price with attention mechanism and bidirectional long short-term memory network," Energy, Elsevier, vol. 299(C).
  10. Ying, Feixiang & Huang, Lingling & Liu, Yang & Fu, Yang, 2026. "Intelligent early fault warning for offshore wind turbine generators: a hybrid deep learning model with causal condition-adaptive dynamic thresholds," Energy, Elsevier, vol. 347(C).
  11. Hongtao Li & Xiaoxuan Li & Shaolong Sun & Zhipeng Huang & Xiaoyan Jia, 2024. "Multivariable forecasting approach of high‐speed railway passenger demand based on residual term of Baidu search index and error correction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2401-2433, November.
  12. Zhao, Yang & Wang, Jianzhou & Wang, Shuai & Zheng, Jingwei & Lv, Mengzheng, 2025. "Using explainable deep learning to improve decision quality: Evidence from carbon trading market," Omega, Elsevier, vol. 133(C).
  13. Liu, Jinpei & Qiu, Biyue & Du, Pengcheng & Zhao, Xiaoman & Zhu, Jiaming, 2025. "A novel probabilistic connectivity network link prediction model for natural gas price based on an improved K-shell algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 671(C).
  14. Chen, Li & Yang, Jibin & Wu, Xiaohua & Deng, Pengyi & Xu, Xiaohui & Peng, Yiqiang, 2025. "Remaining useful life prediction of PEMFCs based on mode decomposition and hybrid method under real-world traffic conditions," Energy, Elsevier, vol. 314(C).
  15. Tianqi Pang & Kehui Tan & Chenyou Fan, 2023. "Carbon Price Forecasting with Quantile Regression and Feature Selection," Papers 2305.03224, arXiv.org.
  16. Yin, Linfei & Zhou, Hang, 2024. "Modal decomposition integrated model for ultra-supercritical coal-fired power plant reheater tube temperature multi-step prediction," Energy, Elsevier, vol. 292(C).
  17. Yingjie Zhu & Yongfa Chen & Qiuling Hua & Jie Wang & Yinghui Guo & Zhijuan Li & Jiageng Ma & Qi Wei, 2024. "A Hybrid Model for Carbon Price Forecasting Based on Improved Feature Extraction and Non-Linear Integration," Mathematics, MDPI, vol. 12(10), pages 1-26, May.
  18. Ding, Jia & Wang, Maolin & Jin, Junyang & Goncalves, Jorge, 2026. "A transformer-based model for carbon price forecasting with self-decomposition," International Review of Financial Analysis, Elsevier, vol. 109(C).
  19. Shang, Dawei & Pang, Yudan & Wang, Haijie, 2025. "Carbon price fluctuation prediction using a novel hybrid statistics and machine learning approach," Energy, Elsevier, vol. 324(C).
  20. Gao, Xifeng & Zang, Yuesong & Ma, Qian & Liu, Mengmeng & Cui, Yiming & Dang, Dazhi, 2025. "A physics-constrained deep learning framework enhanced with signal decomposition for accurate short-term photovoltaic power generation forecasting," Energy, Elsevier, vol. 326(C).
  21. Wang, Yue & Wang, Zhong & Luo, Yuyan, 2024. "A hybrid carbon price forecasting model combining time series clustering and data augmentation," Energy, Elsevier, vol. 308(C).
  22. Zhou, Mingyu & Du, Pei, 2025. "Multivariate events enhanced pre-trained large language model for carbon price forecasting," Energy, Elsevier, vol. 336(C).
  23. Xiangming Kong & Yuetian Liu & Liang Xue & Guanlin Li & Dongdong Zhu, 2023. "A Hybrid Oil Production Prediction Model Based on Artificial Intelligence Technology," Energies, MDPI, vol. 16(3), pages 1-16, January.
  24. Yin, Hao & Yin, Yiding & Li, Hanhong & Zhu, Jianbin & Xian, Zikang & Tang, Yanshu & Xiao, Liexi & Rong, Jiayu & Li, Chen & Zhang, Haitao & Xie, Zhifeng & Meng, Anbo, 2025. "Carbon emissions trading price forecasting based on temporal-spatial multidimensional collaborative attention network and segment imbalance regression," Applied Energy, Elsevier, vol. 377(PA).
  25. Castello, Oleksandr & Resta, Marina, 2025. "Univariate and multivariate forecasting of the electricity futures curve using Dynamic Recurrent Neural Networks," Applied Energy, Elsevier, vol. 394(C).
  26. Sherzod N. Tashpulatov, 2022. "Modeling Electricity Price Dynamics Using Flexible Distributions," Mathematics, MDPI, vol. 10(10), pages 1-15, May.
  27. Cao, Jin-Hui & Xie, Chi & Zhou, Yang & Wang, Gang-Jin & Zhu, You, 2025. "Forecasting carbon price: A novel multi-factor spatial-temporal GNN framework integrating Graph WaveNet and self-attention mechanism," Energy Economics, Elsevier, vol. 144(C).
  28. Xu Xizhen & Liu Yuming & Ou Guoliang, 2026. "Decoupling effect and scenario prediction of carbon emission in transportation industry based on CD-LMDI and CNN-GRU-attention model," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 31(3), pages 1-48, March.
  29. Wenqi Zhang & Zuogong Wang, 2026. "Carbon finance and low-carbon technological change: Evidence from China," Energy & Environment, , vol. 37(1), pages 99-132, February.
  30. Li, Chun & Shi, Jiarong, 2025. "A novel CNN-LSTM-based forecasting model for household electricity load by merging mode decomposition, self-attention and autoencoder," Energy, Elsevier, vol. 330(C).
  31. Bai, Yun & Deng, Shuyun & Pu, Ziqiang & Li, Chuan, 2024. "Carbon price forecasting using leaky integrator echo state networks with the framework of decomposition-reconstruction-integration," Energy, Elsevier, vol. 305(C).
  32. Konstantinos Bisiotis & Dimitris Christopoulos & George Tzougas, 2026. "Forecasting Carbon Prices: A Literature Review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(2), pages 496-529, March.
  33. Qian, Shuangyue & He, Zhuoming & Wan, Ruxing & Tang, Ling, 2026. "A multiscale analysis of spillover effects and price forecasting in China's carbon market," Energy, Elsevier, vol. 347(C).
  34. Pedro Reis & Ana Paula Serra & Jo~ao Gama, 2025. "The Role of Deep Learning in Financial Asset Management: A Systematic Review," Papers 2503.01591, arXiv.org.
  35. Siqiong Dai & Liang Yuan & Jiayi Zhong & Xubin Liu & Zhangjie Liu, 2025. "Forecasting Residential EV Charging Pile Capacity in Urban Power Systems: A Cointegration–BiLSTM Hybrid Approach," Sustainability, MDPI, vol. 17(14), pages 1-18, July.
  36. Lin Wang & Wuyue An & Feng‐Ting Li, 2024. "Text‐based corn futures price forecasting using improved neural basis expansion network," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2042-2063, September.
  37. Zhou, Yilin & Wang, Jianzhou & Wang, Kang & Gao, Jialu & Li, Hongmin & Lu, Haiyan, 2025. "An interpretable analytical framework for carbon price forecasting: Combining multi-source factors and price decomposition," Energy Economics, Elsevier, vol. 152(C).
  38. Yi Xiao & Xianchi Zhang & Chen He & Yi Hu, 2025. "A Hybrid Deep Learning Model for Coal Index Forecasting Based on Sentiment Analysis and Decomposition–Reconstruction Methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(8), pages 2425-2441, December.
  39. Xin, Ling, 2024. "Short-term contrarian in the carbon emission market," Energy Economics, Elsevier, vol. 139(C).
  40. Na Fu & Liyan Geng & Junhai Ma & Xue Ding, 2023. "Price, Complexity, and Mathematical Model," Mathematics, MDPI, vol. 11(13), pages 1-30, June.
  41. Zeyu Zhang & Xiaoqian Liu & Xiling Zhang & Zhishan Yang & Jian Yao, 2024. "Carbon Price Forecasting Using Optimized Sliding Window Empirical Wavelet Transform and Gated Recurrent Unit Network to Mitigate Data Leakage," Energies, MDPI, vol. 17(17), pages 1-22, August.
  42. Chao Zhang & Yihang Zhao & Huiru Zhao, 2022. "A Novel Hybrid Price Prediction Model for Multimodal Carbon Emission Trading Market Based on CEEMDAN Algorithm and Window-Based XGBoost Approach," Mathematics, MDPI, vol. 10(21), pages 1-16, November.
  43. Hang Yin & Zeyu Wu & Junchao Wu & Junjie Jiang & Yalin Chen & Mingxuan Chen & Shixuan Luo & Lijun Gao, 2023. "A Hybrid Medium and Long-Term Relative Humidity Point and Interval Prediction Method for Intensive Poultry Farming," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
  44. Wu, Han & Du, Pei, 2024. "Dual-stream transformer-attention fusion network for short-term carbon price prediction," Energy, Elsevier, vol. 311(C).
  45. Yu, Yue & Chen, Qiyong & Zhi, Jiaqi & Yao, Xiao & Li, Luji & Shi, Changfeng, 2024. "Carbon peak prediction in China based on Bagging-integrated GA-BiLSTM model under provincial perspective," Energy, Elsevier, vol. 313(C).
  46. Han, Kunlun & Yang, Kai & Yin, Linfei, 2022. "Lightweight actor-critic generative adversarial networks for real-time smart generation control of microgrids," Applied Energy, Elsevier, vol. 317(C).
  47. Jujie Wang & Maolin He, 2025. "Extended decomposition ensemble framework based on full data analysis and optimized combination with relaxed boundary for carbon price forecasting," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(1), pages 909-942, January.
  48. Shao, Qihui & Du, Yongqiang & Xue, Wenxuan & Yang, Zhiyuan & Jia, Zhenxin & Shao, Xianzhu & Xu, Xue & Duan, Hongbo & Zhu, Zhipeng, 2024. "Predicting China's thermal coal price: Does multivariate decomposition-integrated forecasting model with window rolling work?," Resources Policy, Elsevier, vol. 99(C).
  49. Bi, Yubo & Wu, Qiulan & Wang, Shilu & Shi, Jihao & Cong, Haiyong & Ye, Lili & Gao, Wei & Bi, Mingshu, 2023. "Hydrogen leakage location prediction at hydrogen refueling stations based on deep learning," Energy, Elsevier, vol. 284(C).
  50. Tian, Yingjie & Wen, Haonan & Guo, Kun, 2025. "Machine learning applications in climate finance: An overview," Research in International Business and Finance, Elsevier, vol. 79(C).
  51. Yin, Linfei & Cao, Xinghui & Liu, Dongduan, 2023. "Weighted fully-connected regression networks for one-day-ahead hourly photovoltaic power forecasting," Applied Energy, Elsevier, vol. 332(C).
  52. Xian, Sidong & Feng, Miaomiao & Cheng, Yue, 2023. "Incremental nonlinear trend fuzzy granulation for carbon trading time series forecast," Applied Energy, Elsevier, vol. 352(C).
  53. Zeng, Qingshun & Shi, Changfeng & Zhu, Wenjun & Zhi, Jiaqi & Na, Xiaohong, 2023. "Sequential data-driven carbon peaking path simulation research of the Yangtze River Delta urban agglomeration based on semantic mining and heuristic algorithm optimization," Energy, Elsevier, vol. 285(C).
  54. Wang, Mie & Ying, Feixiang & Zhu, Yunlou, 2026. "A novel multistep point and interval prediction framework for accurate short-term wave height estimation incorporating the TCN-GRU-Attention model and error distribution analysis," Renewable Energy, Elsevier, vol. 256(PE).
  55. Bin-Bin Zhang & Dongheng Zhang & Yadong Li & Zhi Lu & Jinbo Chen & Haoyu Wang & Fang Zhou & Yu Pu & Yang Hu & Li-Kun Ma & Qibin Sun & Yan Chen, 2024. "Monitoring long-term cardiac activity with contactless radio frequency signals," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  56. Wang, Piao & Tao, Zhifu & Liu, Jinpei & Chen, Huayou, 2023. "Improving the forecasting accuracy of interval-valued carbon price from a novel multi-scale framework with outliers detection: An improved interval-valued time series analysis mode," Energy Economics, Elsevier, vol. 118(C).
  57. Dinggao Liu & Liuqing Wang & Shuo Lin & Zhenpeng Tang, 2025. "A Novel Multi-Task Learning Framework for Interval-Valued Carbon Price Forecasting Using Online News and Search Engine Data," Mathematics, MDPI, vol. 13(3), pages 1-23, January.
  58. Nan Wang & Yuanhao Shi & Fangshu Cui & Jie Wen & Jianfang Jia & Bohui Wang, 2025. "Improving the Heat Transfer Efficiency of Economizers: A Comprehensive Strategy Based on Machine Learning and Quantile Ideas," Energies, MDPI, vol. 18(16), pages 1-31, August.
  59. Xiaohan Cai & Bo Yan, 2025. "Tail Dependence of Liquidity and Volatility in Carbon Futures Market: Evidence From EU ETS," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 46(6), pages 3538-3570, September.
  60. Taorong Jia & Lixiao Yao & Guoqing Yang & Qi He, 2022. "A Short-Term Power Load Forecasting Method of Based on the CEEMDAN-MVO-GRU," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
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  62. Zhang, Ditian & Tang, Pan, 2023. "Forecasting European Union allowances futures: The role of technical indicators," Energy, Elsevier, vol. 270(C).
  63. Yang, Fan & Lee, Hyoungsuk, 2022. "An innovative provincial CO2 emission quota allocation scheme for Chinese low-carbon transition," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
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