鍾萍

1999.9—2002.6中國農業大學數學系,博士

1990.9—1997.6曲阜師範大學數學系學士,碩士 ^[1] 

2009.12-今中國農業大學應用數學系，教授

2003.10—2005.9日本京都大學博士後

2002.12—2009.11中國農業大學應用數學系副教授

1997.7—2002.11中國農業大學數學系助教,講師 ^[1] 

1.國家自然科學基金：基於先驗知識的支持向量機的最優化模型與算法研究，2012.1-2015.12，主持

2.國家自然科學基金：粗糙雙胞胎支持向量機算法的研究及應用，2012.1-2012.12，參加

3.國家自然科學基金：基於優化新技術的支持向量機的模型與算法研究，2007.1-2009.12，主持

4.教育部留學回國人員科研啓動基金：最優化理論的新技術在支持向量機中的應用, 2007.1-2007.12，主持

5.中國農業大學科研啓動基金: 優化新技術在支持向量機中的應用, 2006.1-2007.12,主持

6.國家自然科學基金：數據挖掘中的最優化方法，2004.1-2006.12，主要參加人

7.國家自然科學基金：使用PCG技術的不精確Newton法的理論研究及其應用，2001.1-2003.12,參加

8.中央高校基本業務科研基金“直推式支持向量機模型與算法研究”，2016.1-2016.12，主持 ^[1] 

自1998年以來，發表論文60餘篇。近年來發表的論文：

2017年

1.Huimin Pei,KuainiWang,PingZhong*,Semi-supervised matrixized least squares support vector machine,Applied Soft Computing,Accepted, 2017. (SCI，ESI前10%)

2.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)

3.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%)

4. Wenxin Zhu,Ping Zhong*,Minimum Class Variance SVM+ for Data Classification,Advances in Data Analysis and Classification, 11:79-96, 2017（SCI ）

2016年

1.Yanyan Chen, Kuaini Wang,Ping Zhong*,Oneclasssupporttensormachine,Knowledge-Based Systems, 96:14–28, 2016. (SCI，ESI前10%)

2.Jing Jing Zhang,Ping Zhong*, Least squares one-class support vector machine on fuzzy set.International Journal ofControl and Automation, 9(12): 249-260 2016.

3.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)

4.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)

5.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)

2015年

1. Kuaini Wang, Wenxin Zhu andPing Zhong*. Robust support vector regression withgeneralized Loss Function and Applications,Neural Processing Letters,41:89–106, 2015. (SCI )

2. Jingjing Zhang, .Kuaini Wang, Wenxin Zhu andPing Zhong*,Least squares fuzzy one-class support vector machine for imbalanced data,International Journal of Signal Processing, Image Processing and PatternRecognition, 8(8): 299-308, 2015. (EI)

2014年

1.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%)

2.Wenxin Zhu,Ping Zhong*. A new one-class SVM based on hidden information,Knowledge-Based Systems, 60 : 35–43,2014. (SCI, ESI前10%)

3.Kuaini Wang, Jingjing Zhang, Yanyan Chen,Ping Zhong*, Least Absolute Deviation Support Vector Regression,Mathematical Problems in Engineering, Volume 2014, Article ID 169575 (SCI)

4.Kuaini Wang,Ping Zhong*, Robust support vector regression with flexible loss function,InternationalJournal of Signal Processing, Image Processing and PatternRecognition, 7(4): 211-220, 2014. (EI)

5.Kuaini Wang, ZhiquanHan, Shuli Cui,Ping Zhong*, Flood runoff prediction using LS-SVR based onsliding time window.Journal of Information and Computational Science, vol.11 (2): 641-647, 2014.(EI)

6. 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)

2013年

1. Yaohong Zhao, Jun liu,PingZhong*, Kuaini Wang, Sparse multiple kernel for least square support vector regression,Journal of Computaional Information Systems, 9(23):9593-9599, 2013 (EI)

2. 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)

2012年

1.Ping Zhong*,Training robust support vector regression with smooth non-convex loss function,Optimization Methods andSoftware, 27(6): 1039-1058, 2012. (SCI )

2.Ping Zhong*,Yitian Xu, Yaohong Zhao, Training twin support vector regression via linear programming,Neural Computing and Applications, 21(2): 399–407, 2012. (SCI)

3.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)

4.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)

5.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)

6. 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) ^[1] 

主要講授線性代數(本科生課程)，支持向量機(研究生課程)，長期參加線性代數重點課程建設。 《線性代數輔導教材》, 中國農業出版社，副主編，2009年.《高等數學》，科學技術文獻出版社，副主編，2004年.

指導北京市大學生創新項目一項, 指導本科生URP一項。 ^[1]  .

趙耀紅北京市優秀博士研究生畢業生；中國農業大學博士生科研成就獎；中國農業大學“三好研究生”稱號；中國農業大學優秀研究生黨員；中國農業大學博士研究生科研創新專項NO.KYCX2010105。

王快妮研究生國家獎學金；北京市優秀博士研究生畢業生；中國農業大學研究生三好學生；中國農業大學博士研究生科研創新專項NO.2013YJ010。

張靜靜中國農業大學博士一等學業獎學金。

劉俊中國農業大學研究生學習優秀獎學金；中國農業大學理學院優秀研究生黨員。

裴慧敏2015年、2016年博士二等學業獎學金。

盧立雲2016年碩士二等學業獎學金。 ^[1]