Wind speed forecasting based on variational mode decomposition and improved echo state network H Hu, L Wang, R Tao Renewable Energy 164, 729-751, 2021 | 173 | 2021 |
Forecasting energy consumption and wind power generation using deep echo state network H Hu, L Wang, SX Lv Renewable Energy 154, 598-613, 2020 | 145 | 2020 |
Effective electricity energy consumption forecasting using echo state network improved by differential evolution algorithm L Wang, H Hu, XY Ai, H Liu Energy 153, 801-815, 2018 | 116 | 2018 |
Effective energy consumption forecasting using enhanced bagged echo state network H Hu, L Wang, L Peng, YR Zeng Energy 193, 116778, 2020 | 89 | 2020 |
Effective wind power prediction using novel deep learning network: Stacked independently recurrent autoencoder L Wang, R Tao, H Hu, YR Zeng Renewable Energy 164, 642-655, 2021 | 88 | 2021 |
Effective machine learning model combination based on selective ensemble strategy for time series forecasting SX Lv, L Peng, H Hu, L Wang Information Sciences 612, 994-1023, 2022 | 58 | 2022 |
An improved differential harmony search algorithm for function optimization problems L Wang, H Hu, R Liu, X Zhou Soft Computing 23, 4827-4852, 2019 | 56 | 2019 |
Rolling decomposition method in fusion with echo state network for wind speed forecasting H Hu, L Wang, D Zhang, L Ling Renewable Energy 216, 119101, 2023 | 19 | 2023 |
Carbon emission price point-interval forecasting based on multivariate variational mode decomposition and attention-LSTM model L Zeng, H Hu, H Tang, X Zhang, D Zhang Applied Soft Computing 157, 111543, 2024 | 10 | 2024 |
Dual-stage ensemble approach using online knowledge distillation for forecasting carbon emissions in the electric power industry R Lin, X Lv, H Hu, L Ling, Z Yu, D Zhang Data Science and Management 6 (4), 227-238, 2023 | 9 | 2023 |
Multi-step prediction of carbon emissions based on a secondary decomposition framework coupled with stacking ensemble strategy B Zhang, L Ling, L Zeng, H Hu, D Zhang Environmental Science and Pollution Research 30 (27), 71063-71087, 2023 | 7 | 2023 |
A hybrid model for point and interval forecasting of agricultural price based on the decomposition-ensemble and KDE D Zhang, X Zhang, H Hu, B Zhang, L Ling Soft Computing, 1-24, 2024 | 2 | 2024 |
Integrated GCN–BiGRU–TPE Agricultural Product Futures Prices Prediction Based on Multi-graph Construction D Zhang, X Li, L Ling, H Hu, R Lin Computational Economics, 1-29, 2025 | 1 | 2025 |
A drift-aware dynamic ensemble model with two-stage member selection for carbon price forecasting L Zeng, H Hu, Q Song, B Zhang, R Lin, D Zhang Energy 313, 133699, 2024 | | 2024 |
A combined framework for carbon emissions prediction integrating online search attention D Zhang, Z Yu, L Ling, H Hu, R Lin Journal of Intelligent & Fuzzy Systems, 1-16, 2024 | | 2024 |
Carbon Emission Price Point-Interval Forecasting Based on Multivariate Decomposition Technology and Deep Learning Algorithm L Zeng, H Hu, H Tang, X Zhang, D Zhang Available at SSRN 4521915, 0 | | |