Carbon price prediction research based on CEEMDAN-VMD secondary decomposition and BiLSTM DOI
Ming Fang, Yuanliang Zhang, Wei Liang

et al.

Environmental Science and Pollution Research, Journal Year: 2025, Volume and Issue: unknown

Published: March 17, 2025

Language: Английский

Predicting hourly heating load in residential buildings using a hybrid SSA–CNN–SVM approach DOI Creative Commons

Wenhan An,

Bo Gao, Jianhua Liu

et al.

Case Studies in Thermal Engineering, Journal Year: 2024, Volume and Issue: 59, P. 104516 - 104516

Published: May 8, 2024

This study proposes a hybrid prediction model using sparrow search algorithm (SSA) to optimize the convolutional neural network (CNN) and support vector machine (SVM), in order perform accurate of secondary supply temperature (Ts2). The historical operation data Weifang residential building thermal station was adopted reasonable preprocessing performed suppress interference abnormal data. input variables were screened correlation analysis method, taking influence hysteresis effect into consideration. SSA-CNN-SVM then developed for prediction. performance evaluated by root mean square error, absolute percentage error (MAPE), value relative each time step. results obtained demonstrated that has high accuracy. MAPE values two heat exchange stations between 2.28% 2.4%. indoor significantly affected accuracy Ts2. After introduction temperature, predicted reduced 0.35%. maximum reduction 1.5% compared with other models.

Language: Английский

Citations

12
Investigation on the Long Short-term Memory-based Models for Rural Heating Load Prediction in Northeast China DOI
Shengming Dong, Tong Liu, Xiaowei Hu

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134751 - 134751

Published: Jan. 1, 2025

Language: Английский

Citations

1
An integration model enabled deep learning for energy prediction of machine tools DOI
Yang Xie, Yiqun Dai,

Chaoyong Zhang

et al.

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145075 - 145075

Published: Feb. 1, 2025

Language: Английский

Citations

1
Carbon Price Point and Interval-Valued Prediction Based on a Novel Hybrid Model DOI Creative Commons
Haoyu Chen,

Qunli Wu,

C. Han

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(5), P. 1054 - 1054

Published: Feb. 21, 2025

Accurate carbon price forecasting enables the steady operation of trading market and optimal resource allocation while also empowering participants to understand dynamics make informed decisions, ultimately supporting sustainable development in market. While early research primarily focused on point single-value price, recent studies have shifted towards interval prediction, although there is still a lack dedicated developing models for interval-valued predictions. The importance lies its ability better capture upper lower bounds range across different time dimensions, thereby revealing intrinsic patterns trends fluctuations assisting comprehensively volatility. This study offers novel approach based CEEMDAN-CNN-BiLSTM-SENet hybrid model, providing framework both model makes more comprehensive analysis possible by combining predictions from these two approaches. In case using Hubei market’s data, mean absolute percentage error pricing was 0.8125%, with MAPE highest lowest prices being 1.8898% 1.7852%, respectively—both outperforming other comparative models. results demonstrate that this can measure effectively.

Language: Английский

Citations

1
Prediction of submarine soil dredging difficulty scale in cutter suction dredger construction with clustering-based deep learning DOI
Yong Chen, Qiubing Ren, Mingchao Li

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 147, P. 110370 - 110370

Published: Feb. 27, 2025

Language: Английский

Citations

1
Framework for multivariate carbon price forecasting: A novel hybrid model DOI

Xuankai Zhang,

Ying Zong,

Pei Du

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 369, P. 122275 - 122275

Published: Aug. 31, 2024

Language: Английский

Citations

8
Forecast combination using grey relational analysis and Choquet fuzzy integral for container throughput forecasting DOI
Geng Wu, Yi‐Chung Hu,

Yu‐Jing Chiu

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 252, P. 124170 - 124170

Published: May 6, 2024

Language: Английский

Citations

7
Carbon price forecasting using leaky integrator echo state networks with the framework of decomposition-reconstruction-integration DOI
Yun Bai, Shuyun Deng,

Ziqiang Pu

et al.

Energy, Journal Year: 2024, Volume and Issue: 305, P. 132338 - 132338

Published: July 6, 2024

Language: Английский

Citations

6
Breaking through the limitation of carbon price forecasting: A novel hybrid model based on secondary decomposition and nonlinear integration DOI

Yuqiao Lan,

Yubin Huangfu, Zhehao Huang

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 362, P. 121253 - 121253

Published: June 1, 2024

Language: Английский

Citations

5
A non-destructive detection method of protein and TVB-N content changes in refrigerated and frozen-thawed salmon fillets using fluorescence hyperspectral technology DOI
Zhiyong Zou, Meng-Hua Li, Qianlong Wang

et al.

Journal of Food Composition and Analysis, Journal Year: 2024, Volume and Issue: 133, P. 106435 - 106435

Published: June 14, 2024

Language: Английский

Citations

5