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方红庆

领域:新一代信息技术产业 学校:河海大学职称:副教授

[1] 智能家居环境中人类活动的学习与识别算法
[2] 水力机组控制及其过渡过程
[3] 非线性控制
[4] 群智能优化算法
...

具体了解该专家信息,请致电:027-87555799 邮箱 haizhi@uipplus.com

教育背景

  • 1994.09-1998.07,河海大学,水利水电工动力工程,学士学位
  • 2002.03-2005.12,河海大学,水利水电工程,博士学位

工作经历

1998.08-2000.06,山西省水利水电勘测设计研究院2005.12-,河海大学电气工程学院

项目课题经历

论文、成果、著作等

  • 1、Recurrent Neural Network for Human Activity Recognition in Smart Home,Proceedings of 2013 Chinese Intelligent Automation Conference,2013-01-01,能源与电气学院
  • 2、Influence of time and length size feature selections for human activity sequences recognition,ISA Transactions,2013-01-01,能源与电气学院
  • 3、Recurrent neural network for human activity recognition in smart home,Lecture Notes in Electrical Engineering,2013-01-01,能源与电气学院
  • 4、Application of an improved PSO algorithm to optimal tuning of PID gains for water turbine governor,Energy Conversion and Management,2011-01-01,能源与电气学院
  • 5、Intelligent Optimal Tuning of Hydraulic Turbine Governor PID Gains Based on Nonlinear Model,IEEE计算机科学与服务系统国际会议论文集,2011-01-01,能源与电气学院
  • 6、Feature Selections for Human Activity Recognition in Smart Home Environments,International Journal of Innovative Computing, Information and Control,2012-01-01,能源与电气学院
  • 7、BP Neural Network for Human Activity Recognition in Smart Home,IEEE计算机科学与服务系统国际会议,2012-01-01,能源与电气学院
  • 8、An improved position prediction algorithm based on Active LeZi in Smart Home,IEEE计算机科学与服务系统国际会议,2012-01-01,能源与电气学院
  • 9、BP neural network for human activity recognition in smart home,Proceedings - 2012 International Conference on Computer Science and Service System CSSS 2012,2012-01-01,能源与电气学院
  • 10、基于线性与非线性模型的水轮机调速器PID参数优化比较,中国电机工程学报,2010-01-01,能源与电气学院
  • 11、Application of an enhanced PSO algorithm to optimal tuning of PID gains,2009 Chinese Control and Decision Conference,2009-01-01,能源与电气学院
  • 12、A novel PSO algorithm for global optimization of multi-dimensional function,2008中国控制与决策会议,2008-01-01,能源与电气学院
  • 13、Comparison of PSO algorithm and its variants to optimal parameters of PID controller,2008中国控制与决策会议,2008-01-01,能源与电气学院
  • 14、一种改进粒子群算法及其在水轮机控制器PID参数优化中的应用,南京理工大学学报(自然科学版),2008-01-01,能源与电气学院
  • 15、Basic Modeling and Simulation Tool for Analysis of Hydraulic Transients in Hydroelectric Power Plants,IEEE Transactions on Energy Conversion,2008-01-01,能源与电气学院
  • 16、非线性非最小相位系统伪线性复合控制,南京理工大学学报(自然科学版),2005-01-01,水利水电学院
  • 17、Modeling and Simulation of Hydraulic Transients for Hydropower Plants,Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference,2005-01-01,能源与电气学院
  • 18、Optimal hydraulic turbogenerators PID governor tuning with an improved particle swarm optimization algorithm,中国电机工程学报,2005-01-01,能源与电气学院
  • 19、基于改进粒子群算法的水轮发电机组PID调速器参数优化,中国电机工程学报,2005-01-01,能源与电气学院
  • 20、Comparison of Different Integral Performance Criteria for Optimal Hydro Generator Governor Tuning with a Particle Swarm Optimization Algorithm,Lecture Notes in Computer Science,2007-01-01,能源与电气学院
  • 21、Nonlinear control for hydro turbine generator unit with time-varying parameters via state feedback linearization,2004 8TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION, VOLS 1-3,2004-01-01,能源与电气学院
  • 22、Dynamic real-time simulator for hydraulic turbine generating unit based on programmable computer controller,IECON Proceedings (Industrial Electronics Conference),2004-01-01,能源与电气学院
  • 23、High Performance Hydraulic Turbine Governor Based on Programmable Computer Controller,Proccedings of the 2004 International Conference on Dynamics, Instrumentation and Control,2004-01-01,能源与电气学院
  • 24、基于面向对象技术的水电站数字仿真,扬州大学学报(自然科学版),2003-01-01,水利水电学院
  • 25、水轮机调节系统非线性扰动解耦控制,中国电机工程学报,2004-01-01,水利水电学院
  • 26、水轮机调节系统控制策略综述,人民长江,2004-01-01,水利水电学院
  • 27、Recognizing Human Activity in Smart Home Using Deep Learning algorithm,Proceedings of the 33rd Chinese Control Conference,2014-07-28,能源与电气学院
  • 28、Human activity recognition based on feature selection in smart home using back-propagation algorithm,ISA Transactions,2014-09-30,能源与电气学院
  • 29、Speed Governor PID Gains Optimal Tuning of Hydraulic Turbine Generator Set with An Improved Artificial Fish Swarm Algorithm,Proceedings of the IEEE International Conference on Information and Automation,2016-08-03,能源与电气学院
  • 30、Real-time human activity recognition in smart home with binary tree SVM,Proceedings of the 35th Chinese Control Conference,2016-07-27,能源与电气学院
  • 31、Maximal relevance feature selection for human activity recognition in smart home,The 30th Chinese Control and Decision Conference,2018-06-09,能源与电气学院
  • 32、Active–disturbance–rejection–control and fractional–order–proportional–integral–derivative hybrid control for hydroturbine speed governor system,Measurement and Control,2018-05-29,能源与电气学院

专利、著作版权等

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