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一、个人简介
杨阔，男， 1995年出生，汉，籍贯：河南信阳；博士，雷竞技电竞平台官网雷竞技电竞平台官网讲师。
二、主要学习与工作经历
主要学习经历：
2014.9-2018.7 雷竞技电竞平台官网 车辆工程专业 本科
2018.9–2023.8 上海大学 机械电子工程专业 博士研究生
2019.9-2019.12 法国特鲁瓦科技大学 项目访学
主要工作经历：
2023.9-至今，雷竞技电竞平台官网 教师
三、主要科研工作与成绩
近年来在Energy、Renewable and Sustainable Energy Reviews等国内外期刊发表了论文24篇，其中SCI收录15篇，中科院一区9篇，高被引论文一篇，19年至今总被引超过900余次，单篇被引最高190余次,担任International Journal of Electrical Power and Energy，Journal of Energy Chemistry等多个期刊审稿人。
近年主要代表论文：
[1]Liu Zixi, Guanqiang Ruan, Yupeng Tian, Xing Hu, An Zhongxun, Kuo Yang*.Application of a Transformer Network Based on Multi-Scale Branches and Fast Fourier Gating Mechanism in the State of Charge Prediction for Sodium-Ion Batteries，Expert Systems With Applications,2025（通讯作者，SCI一区，IF=7.5)
[2]Kuo Yang, Cai Y, Cheng J. A deep learning model based on multi-attention mechanism and gated recurrent unit network for photovoltaic power forecasting[J]. Computers and Electrical Engineering, 2025, 123: 110250.（SCI三区，IF=7.5)
[3] Liu Zixi, Guanqiang Ruan, Yupeng Tian, Xing Hu, Yan Rong, Kuo Yang*. A real-world battery state of charge prediction method based on a lightweight mixer architecture. Energy, 2024, 311: 133434. （通讯作者，SCI一区，IF=9)
[4] Kuo Yang, Yugui Tang, Shujing Zhang, Zhen Zhang*. A deep learning approach to state of charge estimation of lithium-ion batteries based on dual-stage attention mechanism[J]. Energy, 2022, 244: 123233.(SCI一区，IF=9，ESI高被引论文)
[5] Kuo Yang, Yanyu Wang, Yugui Tang, Zhen Zhang*. Atemporalconvolutionandgatedrecurrentunitnetworkwithattentionforstateofchargeestimationoflithium-ionbatteries[J]. Journal of Energy Storage, 2023, 72: 108774.(SCI二区，IF=8.9)
[6] Ruan Guanqiang, Liu Zixi., Cheng Jinrun, Hu Xing, Chen Song, Liu Shiwen, Yong Guo, Kuo Yang*. A deep learning model for predicting the state of energy in lithium-ion batteries based on magnetic field effects. Energy, 2024, 304, 132161.(通讯作者，SCI一区，IF=9，引用次数4)
[7] Kuo Yang, Yugui Tang, Zhen Zhang*. Parameter identification and state-of-charge estimation for lithium-ion batteries using separated time scales and extended Kalman filter[J]. Energies, 2021, 14(4). (SCI四区，IF=4)
[8] Kuo Yang, Zhen Zhang. Real-timepatternrecognitionforhandgesturebasedon ANN andsurfaceEMG[J]. Proceedingsof2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2019, 2019: 799–802.(EI收录)
[9] Yugui Tang, Kuo Yang, Zhang S. Wind power forecasting: A temporal domain generalization approach incorporating hybrid model and adversarial relationship-based training[J]. Applied Energy, 2024, 355: 122266.(SCI一区，IF=10.1)
[10] Yugui Tang, Kuo Yang, Yichu Zheng, Li Ma, Shujing Zhang, Zhen Zhang. Wind power forecasting: A transfer learning approach incorporating temporal convolution and adversarial training[J]. Renewable Energy, 2024: 12.(SCI一区，IF=9)
[11] Yugui Tang, Kuo Yang, Shujing Zhang, Zhen Zhang. Photovoltaic power forecasting: A dual-attention gated recurrent unit framework incorporating weather clustering and transfer learning strategy[J]. Engineering Applications of Artificial Intelligence, 2024, 130: 107691.(SCI二区，IF=8)
[12] Yugui Tang, Kuo Yang, Shujing Zhang, Zhen Zhang*. Wind power forecasting:A hybrid forecasting model and multi-task learning-based framework[J]. Energy, 2023: 127864.(SCI一区，IF=9)
[13] Yugui Tang, Kuo Yang, Shujing Zhang, Zhen Zhang. Photovoltaic power forecasting: A hybrid deep learning model incorporating transfer learning strategy[J]. Renewable and Sustainable Energy Reviews, 2022, 162(4): 112473.(SCI一区，IF=16.3)
[14] Yugui Tang, Kuo Yang, Shujing Zhang, Zhen Zhang. Early prediction of lithium-ion battery lifetime via a hybrid deep learning model[J]. Measurement, 2022, 199(6): 111530.(SCI二区，IF=5.2)
近五年主持和参与的主要科研项目：
（1）项目来源：上海市科技创新行动计划启明星（扬帆专项），极限工况下基于数据驱动的钠离子动力电池退化机理和寿命预测方法研究,2024-2027,项目负责人
（2）项目来源：上海市基础研究重大项目,多源融合神经信号传感器件新结构设计与感知机理研究,2018-2020,主要参与人
（3）项目来源：国网山东省电力公司电力科学研究院，规模化分布式发电并网状态评估技术研究,2020-2022,主要参与人。
四、主要研究方向
动力电池管理系统，深度学习在储能领域应用、电池荷电状态及寿命状态预测，时序预测算法。
五、招生专业领域
085500机械（专硕）
五、联系方式
邮箱：yangkuo@sdju.edu.cn
