序号

姓名

学号

院（系）

专业

学术成果

1

高明

202011002583

电力学院

电子信息

[1] Gao M ,Li M ,Ji T , et al.  Key Technologies of Intelligent Question-Answering System for Power System Rules and Regulations Based on Improved BERTserini Algorithm [J].  Processes, 2023, 12 (1):

[2] Gao, Ming ; Ji, Tianyao, et al. Research on semantic matching algorithm of BERT intelligent question answering system[C]//Journal of Physics: Conference Series.SPIE Publishing, 2023, 12703: 127032A.

[3] Gao, Ming ; Ji, Tianyao, et al. Application of BERT-based local optimization algorithm in intelligent question answering system design[C]///Journal of Physics: Conference Series.SPIE Publishing, 2023,  12703: 1270329.

[4] Gao M, Zhang W. Power transmission line anomaly detection scheme based on CNN-transformer model[J]. International Journal of Grid and Utility Computing, 2021, 12(4): 388-395.

1.高明,李梦诗,季天瑤,等.一种基于Bert模型的电力安全规程智能问答方法及系统[P].广东省:CN202311467507.3,2024-04-02.

2.高明,李梦诗,季天瑤,等.一种基于特征向量稀疏性的文本分类方法[P].广东省:CN202410315789.3,2024-04-26.

2

陈俊斌

202011002667

电力学院

电子信息

1. Junbin Chen, Tao Yu, Zhenning Pan, et al. Stochastic dynamic power dispatch with human knowledge transfer using Graph-GAN assisted inverse reinforcement learning[J]. IEEE Transactions on Smart Grid. 2024, 15(3): 3303-3315.

2. Junbin Chen, Tao Yu, Zhenning Pan, et al. A scalable graph reinforcement learning algorithm based stochastic dynamic dispatch of power system under high penetration of renewable energy[J]. International Journal of Electrical Power & Energy Systems, 2023, 152: 109212.

3. 陈俊斌,余涛,潘振宁.面向主动配电网实时优化调度的图强化学习方法[J/OL].控制理论与应用:1-9[2024-06-05]. http://kns.cnki.net/kcms/detail/44.1240.tp.20231114.1419.062.html.

4. 陈俊斌,余涛. 配电变压器台区负荷预测方法、系统、装置及介质[P]. 广东省：CN202110752204.0,2022-06-14.

5. 陈俊斌,邓柏荣,余涛. 电力系统调度业务辅助决策方法、系统、装置和存储介质[P]. 广东省：CN202111044795.2,2022-12-16.