Publications

M²FMoE: Multi-Resolution Multi-View Frequency Mixture-of-Experts for Extreme-Adaptive Time Series Forecasting

Yaohui Huang and Runmin Zou and Yun Wang and Laeeq Aslam and Ruipeng Dong

(Oral Presentation)

Proceedings of the 40th AAAI Conference on Artificial Intelligence, 2026 CCF A

Paper Code

Time Series Forecasting Mixture-of-Experts Extreme Regression

@inproceedings{conference/aaai2026/Huang,
  title = {M<sup>2</sup>FMoE: Multi-Resolution Multi-View Frequency Mixture-of-Experts for Extreme-Adaptive Time Series Forecasting},
  author = {Yaohui Huang and Runmin Zou and Yun Wang and Laeeq Aslam and Ruipeng Dong},
  booktitle = {Proceedings of the 40th AAAI Conference on Artificial Intelligence},
  publisher = {},
  year = {2026},
  volume = {},
  number = {},
  pages = {},
  doi = {},
  url = {https://arxiv.org/abs/2601.08631},
  address = {},
  month = {}
}

An End-to-End Ensemble Learning Approach for Enhancing Wind Power Forecasting

Yun Wang and Houhua Xu and Yaohui Huang# and Fan Zhang# and Hongbo Kou and Runmin Zou and Qinghua Hu and Dipti Srinivasan

IEEE Transactions on Sustainable Energy, 2025 JCR Q1

Paper

Wind Power Forecasting Ensemble Learning Dempster-Shafer Theory

@article{journal/tste2025/Wang,
  title = {An End-to-End Ensemble Learning Approach for Enhancing Wind Power Forecasting},
  author = {Yun Wang and Houhua Xu and Yaohui Huang and Fan Zhang and Hongbo Kou and Runmin Zou and Qinghua Hu and Dipti Srinivasan},
  journal = {IEEE Transactions on Sustainable Energy},
  year = {2025},
  volume = {},
  number = {},
  pages = {1-14},
  doi = {10.1109/TSTE.2025.3582425},
  url = {https://ieeexplore.ieee.org/abstract/document/11048619}
}

Causality-Aware Multi-Graph Convolutional Networks With Critical Node Dynamics for Electric Vehicle Charging Station Load Forecasting

Yaohui Huang and Senzhen Wu and Zhijin Wang and Xiufeng Liu and Chendan Li and Yue Hu

IEEE Transactions on Smart Grid, 2025 JCR Q1

Paper

Load Forecasting EVCS Causal Inference

@article{journal/tsg2025/Huang,
  title = {Causality-Aware Multi-Graph Convolutional Networks With Critical Node Dynamics for Electric Vehicle Charging Station Load Forecasting},
  author = {Yaohui Huang and Senzhen Wu and Zhijin Wang and Xiufeng Liu and Chendan Li and Yue Hu},
  journal = {IEEE Transactions on Smart Grid},
  year = {2025},
  volume = {16},
  number = {4},
  pages = {3210-3225},
  doi = {10.1109/TSG.2024.3641234},
  url = {https://ieeexplore.ieee.org/abstract/document/11007094}
}

Multi-Scale Temporal Representation with Sparse Dynamic Graph Learning for District Heat Load Forecasting

Yaohui Huang* and Peisong Zhang* and Zhenkun Lu and Zhikai Ni

Energy, 2025 JCR Q1

Paper

Load Forecasting Multi-scale Sparse Learning

@article{journal/energy2025/Huang,
  title = {Multi-Scale Temporal Representation with Sparse Dynamic Graph Learning for District Heat Load Forecasting},
  author = {Yaohui Huang and Peisong Zhang and Zhenkun Lu and Zhikai Ni},
  journal = {Energy},
  year = {2025},
  volume = {333},
  number = {},
  pages = {136838},
  doi = {https://doi.org/10.1016/j.energy.2025.136838},
  url = {https://www.sciencedirect.com/science/article/pii/S0360544225024806}
}

Sparse Dynamic Graph Learning for District Heat Load Forecasting

Yaohui Huang* and Yuan Zhao* and Zhijin Wang and Xiufeng Liu and Yonggang Fu

Applied Energy, 2024 JCR Q1

Paper

Graph Neural Networks Load Forecasting Sparse Learning

@article{journal/apen2024/Huang,
  title = {Sparse Dynamic Graph Learning for District Heat Load Forecasting},
  author = {Yaohui Huang and Yuan Zhao and Zhijin Wang and Xiufeng Liu and Yonggang Fu},
  journal = {Applied Energy},
  year = {2024},
  volume = {371},
  number = {},
  pages = {123685},
  doi = {},
  url = {https://www.sciencedirect.com/science/article/pii/S0306261924010687}
}

Multiscale Spatio-Temporal Enhanced Short-term Load Forecasting of Electric Vehicle Charging Stations

Zongbao Zhang and Jiao Hao and Wenmeng Zhao and Yan Liu and Yaohui Huang# and Xinhang Luo

AEEES, 2024 EI

Paper

Graph Neural Networks Load Forecasting Electric Vehicle

@inproceedings{conference/aeees2024/Zhang,
  title = {Multiscale Spatio-Temporal Enhanced Short-term Load Forecasting of Electric Vehicle Charging Stations},
  author = {Zongbao Zhang and Jiao Hao and Wenmeng Zhao and Yan Liu and Yaohui Huang and Xinhang Luo},
  booktitle = {AEEES},
  publisher = {{IEEE}},
  year = {2024},
  volume = {},
  number = {},
  pages = {1180-1185},
  doi = {10.1007/978-3-031-08530-7_11},
  url = {https://ieeexplore.ieee.org/document/10544962},
  address = {Chengdu, China},
  month = {March}
}

Carbon Futures Price Forecasting Based on Feature Selection

Yuan Zhao* and Yaohui Huang* and Zhijin Wang and Xiufeng Liu

Engineering Applications of Artificial Intelligence, 2024 JCR Q1 CCF C

Paper

Energy Economics Feature Selection Importance Measurement

@article{journal/eaai2024/Zhao,
  title = {Carbon Futures Price Forecasting Based on Feature Selection},
  author = {Yuan Zhao and Yaohui Huang and Zhijin Wang and Xiufeng Liu},
  journal = {Engineering Applications of Artificial Intelligence},
  year = {2024},
  volume = {135},
  number = {},
  pages = {108646},
  doi = {10.1016/j.engappai.2024.108646},
  url = {https://www.sciencedirect.com/science/article/pii/S0952197624008042}
}

A New Feature Selection Method Based on Importance Measures for Crude Oil Return Forecasting

Yuan Zhao* and Yaohui Huang* and Zhijin Wang and Xiufeng Liu

Neurocomputing, 2024 JCR Q1 CCF C

Paper

Energy Economics Feature Selection Importance Measurement

@article{journal/neucom2024/Zhao,
  title = {A New Feature Selection Method Based on Importance Measures for Crude Oil Return Forecasting},
  author = {Yuan Zhao and Yaohui Huang and Zhijin Wang and Xiufeng Liu},
  journal = {Neurocomputing},
  year = {2024},
  volume = {581},
  number = {},
  pages = {127470},
  doi = {10.1016/j.neucom.2024.127470},
  url = {https://www.sciencedirect.com/science/article/pii/S0925231224002418}
}

Explainable District Heat Load Forecasting with Active Deep Learning

Yaohui Huang* and Yuan Zhao* and Zhijin Wang and Xiufeng Liu and Hanjing Liu and Yonggang Fu

Applied Energy, 2023 JCR Q1

Paper

Graph Neural Networks Active Learning Load Forecasting

@article{journal/apen2023/Huang,
  title = {Explainable District Heat Load Forecasting with Active Deep Learning},
  author = {Yaohui Huang and Yuan Zhao and Zhijin Wang and Xiufeng Liu and Hanjing Liu and Yonggang Fu},
  journal = {Applied Energy},
  year = {2023},
  volume = {350},
  number = {},
  pages = {121753},
  doi = {},
  url = {https://www.sciencedirect.com/science/article/pii/S0306261923011170}
}

An Oriented Attention Model for Infectious Disease Cases Prediction

Peisong Zhang and Zhijin Wang and Guoqing Chao and Yaohui Huang and Jingwen Yan

(Best Special Session Paper Award)

IEA/AIE, 2022 EI

Paper

Infectious Disease Attention Mechanism

@inproceedings{conference/ieaaie2022/Zhang,
  title = {An Oriented Attention Model for Infectious Disease Cases Prediction},
  author = {Peisong Zhang and Zhijin Wang and Guoqing Chao and Yaohui Huang and Jingwen Yan},
  booktitle = {IEA/AIE},
  publisher = {Springer},
  year = {2022},
  volume = {13343},
  number = {},
  pages = {},
  doi = {10.1007/978-3-031-08530-7_11},
  url = {https://link.springer.com/chapter/10.1007/978-3-031-08530-7_11},
  address = {Kitakyushu, Japan},
  month = {July}
}

HFMD Cases Prediction using Transfer One-step-ahead Learning

Yaohui Huang and Peisong Zhang and Ziyang Wang and Zhenkun Lu and Zhijin Wang

Neural Processing Letters, 2023 JCR Q3 CCF C

Paper

Infectious Disease Transfer Learning

@article{journal/nepl2022/Huang,
  title = {HFMD Cases Prediction using Transfer One-step-ahead Learning},
  author = {Yaohui Huang and Peisong Zhang and Ziyang Wang and Zhenkun Lu and Zhijin Wang},
  journal = {Neural Processing Letters},
  year = {2023},
  volume = {55},
  number = {3},
  pages = {2321 -- 2339},
  doi = {10.1007/s11063-022-10795-9},
  url = {http://doi.org/10.1007/s11063-022-10795-9}
}