个人信息：

黄超博士，哈尔滨工业大学学士（2011），法国贡比涅技术大学硕士（2013），香港城市大学博士（2017），香港城市大学博士后（2018）。

研究方向：

数据挖掘 计算智能 智慧能源

依托顺德创新学院科研项目：

基于智能计算的分布式光伏发电工业园区能量管理关键算法研究，广东省基础与应用基础研究基金省市联合基金-青年项目，2020.1.1-2021.12.31，项目负责人；

大数据驱动的风电机组动态发电性能监测技术，北京科技大学顺德创新学院科技创新专项,2020.1.1-2021.12.31，参与；

大数据驱动的智能光伏楼宇能量管理技术，北京科技大学顺德创新学院科技创新专项,2021.1.1-2022.12.31，项目负责人；

数据驱动的阿尔兹海默病早期预测与干预控制研究，北京科技大学顺德创新学院科技创新专项,2021.9.1-2023.8.31，参与；

面向CT影像数据的急性缺血性卒中梗死灶分割模型研究，北京科技大学顺德创新学院科技创新专项,2021.9.1-2023.8.31，参与。

代表性成果：

代表性论文

1) Chao Huang, Hongcai Zhang*, Yonghua Song, Long Wang, Tanveer Ahmad, and Xiong Luo, “Demand Response for Industrial Micro-Grid Considering Photovoltaic Power Uncertainty and Battery Operational Cost”, IEEE Transactions on Smart Grid, vol. 12, no. 4, pp. 3043-3055, 2021.

2) Chao Huang, Hongcai Zhang*, Long Wang, Xiong Luo, Yonghua Song, “Mixed deep reinforcement learning considering discrete-continuous hybrid action space for smart home energy management”, Journal of Modern Power Systems and Clean Energy, vol. 10, no. 3, pp.743-754, 2022.

3) C. Huang, L Wang*, and L. L. Lai, “Data-driven Short-term Solar Irradiance Forecasting Based on Information of Neighboring Sites”, IEEE Transactions on Industrial Electronics, vol. 66, no. 12, pp. 9918-9927, 2019.

4) C. Huang, L. Wang, R. S. C. Yeung, Z. Zhang*, H. S. H. Chung, and A. Bensoussan, “A prediction model guided Jaya algorithm for the PV system maximum power point tracking,” IEEE Transactions on Sustainable Energy, vol. 9, pp. 45-55, 2018.

5) C. Huang, L. Wang, Z. Zhang*, R. S. C. Yeung, A. Bensoussan, and H. S. H. Chung, “A Novel Spline Model Guided Maximum Power Point Tracking Method for Photovoltaic Systems”, IEEE Transactions on Sustainable Energy, vol. 11, no. 3, pp. 1309-1322, 2020.

6) C. Huang, J. Zhang, L. Cao, L. Wang*, X. Luo, J. Wang, and A. Bensoussan, “Robust Forecasting of River-flow Based on Convolutional Neural Network”, IEEE Transactions on Sustainable Computing, vol. 5, no. 4, pp. 594-600, 2020.

7) C. Huang, Z. Zhang, and L. Wang*, “PSOPruner: PSO-Based Deep Convolutional Neural Network Pruning Method for PV Module Defects Classification”, IEEE Journal of Photovoltaics, vol.12, no. 6, pp. 1550-1558, 2022.

8) H. Yang, C. Huang*, L. Wang, and X. Luo, “An improved encoder-decoder network for ore image segmentation”, IEEE Sensors Journal, vol. 21, no. 10, pp. 11469-11475, 2021.

9) C. Huang*, A. Bensoussan, M. Edesess, and K. L. Tsui, "Improvement in artificial neural network-based estimation of grid-connected photovoltaic power output," Renewable Energy, vol. 97, pp. 838-848, Nov 2016.

10) C. Huang, Z. Zhao, L. Wang, Z. Zhang*, and X. Luo, "Point and Interval Forecasting of Solar Irradiance with an Active Gaussian Process", IET Renewable Power Generation, vol. 14, no. 6, pp. 1020-1030, 2020.

科研业绩

1）国家自然科学基金1项（62002016），主持

2）北京市自然科学基金1项（9204028），主持

3）广东省基础与应用基础基金1项（2019A1515111165），主持