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              教师详情
              • 个人信息
                王龙

                Wang Long

                系      所:
                |计算机科学与技术系|
                职      称:
                副教授  
                职      务:
                办公地点:
                信息楼402
                办公电话:
                电子邮箱:
                lwang@ustb.edu.cn
                本 科 课 程:
                研究生课程:
                科 研 方 向:
                机器学习 数据挖掘 计算机视觉 计算智能 能源信息学
                学术与社会兼职:
                IEEE会员 IEEE Power and Energy Society会员 IEEE Council on RFID会员 IEEE Sensors Council会员 IEEE Systems Council 会员 中国电机工程学会会员 国际期刊IEEE Transactions on Cybernetics, IEEE Transactions on Network Science and Engineering, IET Electronics Letters, Journal of Systems
              • 简   历

                王龙博士yobet体育官网,英国伦敦大学学院(University College London)杰出(Distinction)硕士,香港城市大学博士。主要从事机器学习、数据挖掘和计算机视觉及其工业应用等方面的研究yobet体育官网。现为IEEE、IEEE工业电子学会和中国计算机学会会员,中国计算机学会计算机视觉专委会委员yobet体育官网,是2014年香港政府博士奖学金(Hong Kong PhD Fellowship)获得者。目前担任SCI期刊IEEE Access (IF: 4.098) Canadian Journal of Electrical and Computer Engineering (IF: 1.53) 的副主编,PLOS ONE (IF: 2.776) 的学术编辑、编委yobet体育官网,Intelligent Automation & Soft Computing (IF: 0.79) Water (2.524) 的客座编辑。

              • 代表性论文

                1.    L. Wang, Z. Zhang, and J. Chen, “Short-term Electricity Price Forecasting with Stacked Denoising Autoencoders,” IEEE Transactions on Power Systems, vol. 32, no. 4, July 2017. (IF: 6.807)

                2.    L. Wang, Z. Zhang, H. Long, J. Xu, and R. Liu, “Wind Turbine Gearbox Failure Identification with Deep Neural Networks,” IEEE Transactions on Industrial Informatics, vol. 13, no. 3, pp. 1360-1368, June 2017. (IF: 7.377)

                3.    L. Wang and Z. Zhang, “Automatic Detection of Wind Turbine Blade Surface Cracks Based on UAV-taken Images,” IEEE Transactions on Industrial Electronics, vol. 64, no. 9, 2017. (IF: 7.503)

                4.    L. Wang, Z. Zhang, J. Xu, and R. Liu, “Wind Turbine Blade Breakage Monitoring with Deep Autoencoders,” IEEE Transactions on Smart Grid, vol. 9, no. 4, 2018. (IF: 10.486)

                5.    L. Wang, Z. Zhang, and X. Luo, “A Two-stage Data-driven Approach for Image based Wind Turbine Blade Crack Inspections,” IEEE-ASME Transactions on Mechatronics, vol. 24, no. 3, pp. 1271-1281, 2019. (IF: 4.943)

              • 科研业绩

                香港研究资助局主题研究计划“Safety, Reliability, and Disruption Management of High Speed Rail and Metro Systems”,参与
                香港研究资助局杰出青年学者计划“Scheduling Power Production of Hybrid Power Systems with Data Mining and Computational Intelligence”,参与。
                横向项目:
                丹麦Dong Energy公司项目“Wind Turbine Generation Performance Monitoring with Representation Learning”,主持

              • 获得奖励/专利

                2017年香港城市大学Outstanding Academic Performance Award
                2014年香港政府博士奖学金(Hong Kong PhD Fellowship)
                2014年香港城市大学Chow Yei Ching School of Graduate Studies Entrance Scholarships

              • 计通NEWS
              • 索思
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