站内搜索:
  • 当前位置: 首页 >师资队伍 >教师名录 >副教授 >正文
  • 江河

    日期:2019-02-13 21:56:52   文章点击数: 稿源:

    统计学院教师个人简介情况表

    姓名

    江河

    性别

    出生年月

    1985.6.

    职务/职称

    副教授

    学历/学位

    博士

    博导∕硕导

    硕导

    所学专业

    统计学

    电子邮箱

    jiangsky2005@aliyun.com

    学术研究领域:

    机器学习,数据挖掘,人工智能,高维数据变量选择

    荣誉称号和社会团体兼职

    担任 Energy , Energy conversion and management , Metrica, EJS 等10种期刊的审稿人

    教学情况

    为本科生讲授Bayesian Inference(纯英文授课)和数理金融等课程,为硕士研究生讲授《统计学前沿问题方法介绍》,为外籍博士研究生讲授《High dimensional statistics》。

    科研情况

    江河,海归博士,江西财经大学第九批优秀青年学术人才。本科就读于兰州大学数学基地班(2005-2009),硕士在兰州大学攻读概率论与数理统计专业(2009-2012),师从焦桂梅副教授,博士毕业于美国Florida State University统计系(2012-2015),师从Yiyuan She教授。目前共发表SCI论文19篇,主持国家自然科学基金、江西省自然科学基金等8项。

    1. He Jiang*, Yao Dong,   Structural regularization in quadratic logistic regression model. Knowledge based systems. Accepted,   2019;通讯作者. (SCI 二区, IF: 4.529)

    2. He Jiang, Yao Dong, A   novel model based on square root elastic net and artificial neural network   for forecasting global solar radiation. Complexity.   Research Article (19 pages), Article ID 8135193, 2018. (SCI 一区, IF:1.829, top期刊)

    3. He Jiang, Sparse estimation based on square root nonconvex   optimization in high dimensional data. Neurocomputing   2018;282;122-135. (SCI 二区, IF:3.317)

    4. He Jiang, Model forecasting based on two-stage feature   selection procedure using orthogonal greedy algorithm. Applied soft computing 2018; 63; 110-123. (SCI 二区, IF:3.541)

    5. He Jiang*, Yao Dong; Dimension reduction based on a penalized   kernel support vector machine model. Knowledge   based systems 2017; 138:79-90 通讯作者. (SCI 二区, IF: 4.529)

    6. He Jiang, A novel   approach for forecasting global horizontal irradiance based on sparse   quadratic RBF neural network. Energy Conversion and Management 2017;152:266-280. (SCI 一区, IF6.377top期刊)

    7. He Jiang, Yao Dong, Forecast of hourly global horizontal   irradiance based on Structured Kernel Support Vector Machine: A case study of   Tibet area in China. Energy Conversion   and Management 2017;142:307-321. (SCI 一区,IF6.377, top期刊)

    8. He Jiang, Yao Dong, Global horizontal radiation forecast using   forward regression on a quadratic kernel support vector machine: Case study   of the Tibet Autonomous Region in China. Energy   2017;133:270-283. (SCI 一区,IF4.520top期刊)

    9. He Jiang, Yao DongLing Xiao. A multi-stage   intelligent approach based on an ensemble of two-way Interaction Model for   forecasting the global horizontal radiation of India. Energy Conversion and Management 2017;137:142-154. (SCI 一区,IF6.377top期刊)

    10. He Jiang, Yao Dong. A nonlinear support vector machine model   with hard penalty function based on glowworm swarm optimization for   forecasting daily global solar radiation. Energy   Conversion and Management 2016;126:991-1002. (SCI 一区,IF6.377top期刊)

    11. He Jiang, Jianzhou Wang, Yao Dong, Haiyan Lu. Comprehensive   assessment of wind resources and low-carbon economy policies: An empirical   study in Alxa and Xilin Gol League of Inner Mongolia, China. Renewable & Sustainable EnergyReviews 2015;50:1304-1319. (SCI 一区,IF8.050top期刊)

    12. He Jiang, Yao Dong, Jianzhou Wang, Quqin Li. Haiyan Lu.   Intelligent optimization models based on hard-ridge penalty and RBF for   forecasting global solar radiation. Energy   Conversion and Management 2015;95:42-58. (SCI 一区,IF6.377top期刊)

    13. Yao Dong, He Jiang*. A two-stage regularization method for variable selection and forecasting in high-order interaction model. Complexity. Accepted, 2019;通讯作者 (SCI 一区, IF:1.829, top期刊).

    14. Jianzhou Wang, He Jiang*, Yujie Wu, Yao Dong.   Forecasting solar radiation using an optimized hybrid model by Cuckoo Search   algorithm. Energy. 2015;81;627-644 通讯作者. (SCI一区,  IF: 4.520top期刊)

    15. Yiyuan She, Zhifeng Wang, He Jiang. Group regularized estimation under structural   hierarchy. Journal of the American   Statistical Association (JASA). 2018; 113 (521); 445-454. (统计学 top期刊 IF:2.123)

    16. Jianzhou Wang, Yao Dong, He Jiang. A study on the   characteristics, predictions and polies of China’s eight main power grids. Energy Conversion and Management   2014;86; 818-830. (SCI一区,IF6.377top期刊)

    17. Yao Dong, Jianzhou Wang, He Jiang, Xiaomeng Shi. Intelligent   optimized wind resource assessment and       wind turbines selection in Huitengxile of Inner Mongolia, China. Applied Energy 2013;109;239-253. (SCI一区,IF7.182top期刊)

    18. Yao Dong, Jianzhou Wang, He Jiang, Jie Wu. Short-term electricity price forecast based on   the improved hybrid model. Energy   Conversion and Management 2011;52;2987–2995. (SCI一区,IF: 6.377top期刊)

    19. Jianzhou Wang, Yao Dong, Jie Wu, Ren Mu, He Jiang. Coal production forecast   and low carbon policies     in China. Energy Policy 2011;39; 5970–5979. (SCI一区,  IF: 4.140top期刊)

    主持项目

    n  国家自然科学基金地区项目,71861012,光伏并网发电系统中的短期功率预测与储能容量优化配置研究,29万元,2019/01-2022/12, 在研.

    n  第11批中国博士后特别资助,2018T110654,基于特征选取的短期光伏功率预测与储能容量优化研究,15万元,2019/01-2020/12,在研.

    n    第62批中国博士后科学基金面上资助一等资助,2017M620277,适应复杂天气的光伏发电短期功率预测研究,8万元,2018/01-2019/12,在研.

    n    江西省自然科学基金青年项目, 20181BAB211020, 适应复杂天气的光伏发电短期功率预测与影响因素研究, 6万元, 2019/01-2021/12,   在研.

    n    江西财经大学第九批优秀青年学术人才支持计划, 光伏并网发电系统中的短期功率预测与影响因素研究,6万元,2019/01-2021/12,在研.

    n    江西省博士后研究人员日常经费资助,2017RC38,基于特征选取的光伏发电短期功率预测研究,3万元,2018/01-2019/12,在研.

    n    江西省教育厅科学技术研究项目,GJJ60454,自适应特征提取方法在光伏功率预测模型中的应用研究,2万元,2017/01-2018/12,在研.

    n  江西财经大学2017博士后项目,基于特征选取的光伏发电短期功率预测研究,1万元,2018/01-2019/12,在研.

     

    获奖情况

    江西财经大学第九批优秀青年学术人才

    其它情况

    参加的会议

        特邀报告(Invited   Talk),题目:Model forecasting based on   two-stage feature selection procedure using orthogonal greedy algorithm2019年在2019   International Conference on Soft computing and Machine Learning (SCML2019), 武汉,湖北,2019.

        特邀报告(Invited   Talk),题目:Group   Regularized Estimation under Structural Hierarchy2018年在第四届中国现场统计研究会高维数据统计分会, 南昌, 江西, 2018.

        特邀报告(Invited   Talk),题目:Group   Regularized Estimation under Structural Hierarchy2016年兰州大学数学与统计学院建院70周年系列学术报告,兰州,甘肃,2016.

        特邀报告(Invited   Talk),题目:Group   Regularized Estimation under Structural Hierarchy2014年在波士顿举办的联合统计年会(Joint   Statistical Meeting (JSM), Boston, Massachusetts, August 2014)。

        海报发表与竞速演讲(Poster   and Speed Presentation),题目:Group   Regularized Estimation under Structural Hierarchy2013年美国佛罗里达州立大学统计系举办的国际统计年会(International   year of Statistics, Department of Statistics, Florida State University, Nov   2013)。

    指导学生

    硕士生: 杨烨,郑伟华,熊任

    博士生:Muhammad Asif   Khan (joint with 李志龙教授)