陈豪
陈豪
更新日期:2016-02-24  

   陈豪,博士研究员课题组长。2006年获中国人民解放军国防科学技术大学自动化专业学士学位,2009年在英国获得一等荣誉硕士(Distinction),2013年在英国获得Cybernetic(控制论)专业博士学位,2014年1月至2015年7月在加拿大从事博士后研究。回国前在全球最大的油砂开采和石油炼制公司担任项目首席科学家。2015年8月正式加入中科院海西研究院。现任智能计算与工业大数据课题组组长,福建省复杂动态系统智能辨识与控制重点实验室主任,中国自动化学会数据驱动控制、学习与优化委员会委员。

入选福建省“杰青”;首批福建省引进高层次人才境外B类;首批泉州港湾计划高层次人才团队负责人;福建省五四青年团队负责人;泉州市五四青年奖章个人;中科院“春苗”青年人才;中科院“青促会”会员。目前,主要从事非线性时变系统分析建模、工业大数据挖掘与分析、智能计算方面的研究工作

近年来,主持并参与国家自然科学基金、福建省自然科学基金、福建省科技计划项目、泉州市引进高层次人才团队项目等国家、省部、市及企业合作开发项目近30项。领导团队累计发表学术论文近50篇,其中以第一作者在领域内IEEE Transactions on Cybernetics等主流SCI期刊发表3篇,二区长文6篇。首次提出“在线结构可变的径向基神经网络模型”和针对非线性系统的基于改进MPCA算法设备故障诊断方法,研究特长“在线学习”理论是目前解决复杂时变系统建模问题的核心。申请和授权发明专利36项,登记软件著作权10余项。

  办公电话:0595-68187184 

  办公地址:福建省晋江市罗山街道苏内社区溪东路166号 

  电子邮箱chenhao@fjirsm.ac.cn 

  研究方向:非线性时变系统分析建模、工业大数据挖掘与分析、智能计算 

  招生专业:控制科学与控制理论  

  主要代表性论文:

国际期刊论文: 

· J. Guo, H. Chen*, S. Chen, “Improved Kernel Recursive Least Squares Algorithm based Online Prediction for Nonstationary Time Series”, IEEE SIGNAL PROCESSING LETTERS, DOI: 10.1109/LSP.2020.3011892, 07/2020

· J. hang, H. Chen, S. Chen, X. Hong, “An Improved Mixture of Probabilistic PCA for Nonlinear Data-Driven Process Monitoring”, IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2017.2771229, 12/2017

· H. Chen, Y. Gong, X. Hong and Sheng Chen, “A fast adaptive tunable RBF network for nonstationary systems”, IEEE Transactions on Cybernetics, DOI:10.1109/TCYB.2015.248437810/2015 (控制论方向排名第一,Acceptance Rates: 7%,JCR一区)

· H. Chen, Y. Gong, X. Hong, S. Chen, Adaptive Nonlinear Equalizer Using a Mixture of Gaussian-Based Online Density Estimator”,IEEE Transactions on Vehicular TechnologyDOI:10.1109/TVT.2014.2313458,03/2014

· H. Chen, Y. Gong, and X. Hong: “On-line Modelling with Tunable RBF Network”, IEEE Transactions on Cybernetics, vol.43, no.3, pp.935-947, June 2013 (控制论方向排名第一,Acceptance Rates: 7%,JCR一区)

· H. Chen, Y. Gong, X. Hong and Sheng Chen, “Adaptive Equalizer Using a Mixture of Gaussians Based On-Line Density Estimator”, IEEE Transactions on Vehicular Technology, vol.63, no.9, pp.4265,4276, Nov. 2014 (JCR二区)

· H. Chen, Y. Gong and X. Hong, “A new adaptive multiple modeling approach for non-linear and non-stationary systems”, International Journal of Systems Science. DOI:10.1080/00207721.2014.973926,06/2014 (Impact Factor:2.1)   

  国际会议论文: 

· M. Xu, H. Chen, L. Duan, “A Combined Training Algorithm for RBF Neural Network based on Particle Swarm Optimization and Gradient Descent”, 2020 IEEE 9th Data Driven Control and Learning Systems Conference, Liuzhou, China, November 20-22, 2020

· J. Li, T. Yang, H. Chen*.g, “Link Adaptation in MIMO Systems by Using Machine Learning”, IEEE International Conference on Information and Automation (ICIA 2018), Wuyishan, Fujian, 11-13 August, 1-5, 2018.

· Tangyue Yang, Hao Chen*, Jiangze Li. Multi-objective flexible job-shop scheduling problems with limited resource constraints using nondominated sorting genetic algorithm II. IEEE International Conference on Information and Automation (ICIA 2018), Wuyishan, Fujian, 11-13 August, 1-5, 2018.

· X Hong, H. Chen* and S. Wang, “Sparse least squares support vector regression for nonstationary systems”, IJCNN 2018: International Joint Conference on Neural Networks. 1-8, 08-13 July, 2018.

· P. Cai, H. Chen*, J. Zhang, “An Adaptive Multi-Kernel RBF Model Using State Matching”, 2017 6th Data Driven Control and Learning Systems (DDCLS), Chongqing, 26-27 May, 1-5, 2017.

· J. Zhang, S. Chen, H. Chen*, “Process monitoring based on orthogonal locality preserving projection”, 2017 The 5th International Conference on Enterprise System Beijing, 22-24 September, 2017.

· J. Zhang, H. Chen*, P. Cai, “A modified PCA-based approach for process Monitoring”, 2017 29th Chinese Control And Decision Conference (CCDC), Chongqing, 28-30 May, 2017.   

  特邀国际学术报告: 

· 29th April 2013, ‘‘Real Time Model Adaptation for Non-Stationary Systems’’, (Host: Prof. Xin Yao), School of Computer Science, University of Birmingham, UK,