个人简介
山东省胶州市人。硕士生、博士生导师，主要研究方向为运筹与优化、机器学习和数据挖掘。
个人经历
2009.12-今 中国农业大学应用数学系，教授
2003.10—2005.9 日本京都大学 博士后
2002.12—2009.11 中国农业大学应用数学系 副教授
1999.9—2002.6 中国农业大学数学系,博士
1997.7—2002.11 中国农业大学数学系 助教,讲师
1990.9—1997.6 曲阜师范大学数学系 学士,硕士
基金项目
国家自然科学基金：基于先验知识的支持向量机的最优化模型与算法研究，2012.1-2015.12，主持
国家自然科学基金：粗糙双胞胎支持向量机算法的研究及应用，2012.1-2012.12，参加
国家自然科学基金：基于优化新技术的支持向量机的模型与算法研究，2007.1-2009.12，主持
教育部留学回国人员科研启动基金：最优化理论的新技术在支持向量机中的应用, 2007.1-2007.12，主持
中国农业大学科研启动基金: 优化新技术在支持向量机中的应用, 2006.1-2007.12,主持
国家自然科学基金：数据挖掘中的最优化方法，2004.1-2006.12，主要参加人
国家自然科学基金：使用PCG技术的不精确Newton法的理论研究及其应用，2001.1-2003.12,参加
中央高校基本业务科研基金“直推式支持向量机模型与算法研究”，2016.1-2016.12，主持
教学工作
主要讲授线性代数(本科生课程)，支持向量机(研究生课程)，长期参加线性代数重点课程建设。 《线性代数辅导教材》, 中国农业出版社，副主编，2009年.《高等数学》，科学技术文献出版社，副主编，2004年指导北京市大学生创新项目一项, 指导本科生URP一项
近期论文
查看导师最新文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
Huimin Pei, KuainiWang, Ping Zhong*, Semi-supervised matrixized least squares support vector machine, Applied Soft Computing, Accepted, 2017. (SCI，ESI前10%)
Yanyan Chen,Liyun Lu, Ping Zhong*, One-class support higher order tensor machine classifier, Applied Intelligence, 2017. DOI: 10.1007/s10489-017-0945-9 (SCI)
Huimin Pei, Yanyan Chen, Yankun Wu, Ping Zhong*, Laplacian total margin support vector machine based on within-class scatter, Knowledge-Based Systems, 119:152-165,2017. (SCI，ESI前10%)
Wenxin Zhu, Ping Zhong*, Minimum Class Variance SVM+ for Data Classification, Advances in Data Analysis and Classification, 11:79-96, 2017 （SCI )
Yanyan Chen, Kuaini Wang, Ping Zhong*, One class support tensor machine, Knowledge-Based Systems, 96: 14–28, 2016. (SCI，ESI前10%)
Jing Jing Zhang, Ping Zhong*, Least squares one-class support vector machine on fuzzy set. International Journal of Control and Automation, 9(12): 249-260 2016.
Qiang Lin, Huimin Pei，Kuaini Wang, Ping Zhong* Privacy-preserving one-class support vector machine with vertically partitioned data, International Journal of Multimedia and Ubiquitous Engineering, 11(5),199-208, 2016. (EI)
Qiang Lin, Huimin Pei，Kuaini Wang, Ping Zhong*, Privacy-preserving one-class support vector machine with horizontally partitioned data, International Journal of Signal Processing, Image Processing and Pattern Recognition, 9(9) 333-342, 2016.(EI)
Yanyan Chen, Ping Zhong*，Linear one-class support tensor machine, International Journal of Signal Processing, Image Processing and Pattern Recognition, 9(9) 379-388, 2016.(EI)
Kuaini Wang, Wenxin Zhu and Ping Zhong*. Robust support vector regression with generalized Loss Function and Applications, Neural Processing Letters, 41:89–106, 2015. (SCI )
Jingjing Zhang, .Kuaini Wang, Wenxin Zhu and Ping Zhong*, Least squares fuzzy one-class support vector machine for imbalanced data, International Journal of Signal Processing, Image Processing and Pattern Recognition, 8(8): 299-308, 2015. (EI)
Kuaini Wang, Ping Zhong*, Robust non-convex least squares loss function for regression with outliers, knowledge-Based Systems,71: 290-302, 2014. (SCI, ESI前10% )
Wenxin Zhu, Ping Zhong*. A new one-class SVM based on hidden information, Knowledge-Based Systems, 60 : 35–43,2014. (SCI, ESI前10% )
Kuaini Wang, Jingjing Zhang, Yanyan Chen, Ping Zhong*, Least Absolute Deviation Support Vector Regression, Mathematical Problems in Engineering, Volume 2014, Article ID 169575 (SCI)
Kuaini Wang, Ping Zhong*, Robust support vector regression with flexible loss function, International Journal of Signal Processing, Image Processing and Pattern Recognition, 7(4): 211-220, 2014. (EI)
Kuaini Wang, Zhiquan Han, Shuli Cui, Ping Zhong*, Flood runoff prediction using LS-SVR based on sliding time window. Journal of Information and Computational Science, vol. 11 (2): 641-647, 2014. (EI)
Wenxin Zhu, Kuaini Wang,Ping Zhong*, Improving support vector classification by learning group information hidden in the data, ICIC Express Letters, Part B: Applications, 5(3):781-786, 2014.(EI)
Yaohong Zhao, Jun liu, Ping Zhong*, Kuaini Wang, Sparse multiple kernel for least square support vector regression, Journal of Computaional Information Systems, 9(23):9593-9599, 2013 (EI)
Jun Liu, Wenxin Zhu, Ping Zhong*, A new multi-class support vector algorithm based on privileged infromation, Journal of Information and Computional Science, 10(2):443-450, 2013 (EI)
Ping Zhong*, Training robust support vector regression with smooth non-convex loss function, Optimization Methods and Software, 27(6): 1039-1058, 2012. (SCI )
Ping Zhong*,Yitian Xu, Yaohong Zhao, Training twin support vector regression via linear programming, Neural Computing and Applications, 21(2): 399–407, 2012. (SCI)
Yitian Xu, Laisheng Wang,Ping Zhong, A rough margin-based v-twin support vector machine, Neural Computing and Applications,21 (6): 1307-1317, 2012. (SCI)
Yaohong Zhao, Ping Zhong*, A feature selection method for twin support vector regression, ICIC Express Letters, Part B: Applications, 3(1): 91-98,2012. (EI)
Liyuan Liu, Yohong Zhao, Ping Zhong*,Multiple Instance Classification Based on Least Squares Twin Support Vector Machine, Journal of Convergence Information Technology, 7( 6): 72-77, 2012. (EI)
Liyuan Liu, Jing Chen, Ping Zhong*, Successive Least Squares Support Vector Machine for Multiple Instance Classification, Journal of Information and Computational Science, 9(4): 813-819, 2012. (EI)
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