研究论文
A CNN-LSTM based deep learning model with high accuracy and robustness for carbon price forecasting: A case of Shenzhen's carbon market in China
Hanxiao Shi, Anlei Wei, Xiaozhen Xu, Yaqi Zhu, Hao Hu, Songjun Tang
Northwest University
来源Journal of Environmental Management
年份2024
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学科主题
计算机 / AIStock Market Forecasting Methods
Forecasting Techniques and Applications · Energy Load and Power Forecasting
参考文献 64
Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks
被引 1,676Tara N. Sainath, Oriol Vinyals, Andrew Senior · IEEE International Conference on Acoustics Speech and Signal Processing · 2015
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
被引 11,004Chung, Junyoung, Çağlar Gülçehre, Kyunghyun Cho · arXiv (Cornell University) · 2014
A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
被引 20,447Yoav Freund, Robert E. Schapire · Journal of Computer and System Sciences · 1997
此处列出前 3 条
引用本文 167
Framework for multivariate carbon price forecasting: A novel hybrid model
被引 45Xuankai Zhang, Ying Zong, Pei Du · Journal of Environmental Management · 2024
The Optuna–LightGBM–XGBoost Model: A Novel Approach for Estimating Carbon Emissions Based on the Electricity–Carbon Nexus
被引 35Yuanhang Cai, Jianxin Feng, Yanqing Wang · Applied Sciences · 2024
Wavelet CNN‐LSTM time series forecasting of electricity power generation considering biomass thermal systems
被引 33William Gouvêa Buratto, Rafael Ninno Muniz, Ademir Nied · IET Generation Transmission & Distribution · 2024
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