Profile of Associate Professor Jiang He

    ​Name: Jiang He

    ​Title: Associate Professor

    ​Office Phone: 0791-87656767

    ​Email: jiangsky2005@126.com

1. Introduction

Basic Information:

Jiang He, male, was born in June 1985 and is a native of Shenyang City, Liaoning Province. He obtained a PhD in Statistics from Florida State University where he was guided by Professor Yiyuan. He is currently an associate professor and master supervisor of the School of Statistics, Jiangxi University of Finance and Economics.

Research Directions: Management Statistics, Prediction Theory and Methods and their Application in Power Prediction of Photovoltaic Power Generation

Education Experience:

September 2005-June 2009, Lanzhou University

September 2009-June 2012, Lanzhou University

September 2012-May 2015, Florida State University, USA

Work Experience:

October 2015-November 2018, Jiangxi University of Finance and Economics, Lecturer

January 2019-Present, Jiangxi University of Finance and Economics, Associate Professor

2. Teaching Experience

Courses Taught:

Undergraduate: Bayesian Inference, Mathematical Finance

Postgraduate: Advanced Statistics, Data Mining

Doctoral Students: High Dimensional Statistics

Honors:

Candidate of Jiangxi “Double Thousand Plan”

The 9th Batch of Outstanding Young Talents of Jiangxi University of Finance and Economics

3. Research Achievements

Projects Hosted:

1. Project of the National Natural Science Foundation: “Research on the probabilistic prediction and evaluation system of photovoltaic power robustness based on spatio-temporal correlation”. 2020/01-2022/12.

2. Project of the National Natural Science Foundation: “Research on short-term power prediction and energy storage capacity optimization of grid-connected photovoltaic power generation system”. 2019/01-2022/12.

3. Talent Project of Jiangxi “Double Thousand Plan”: “Online probability prediction of photovoltaic power based on uncertainty feature mining”. 2020/01-2022/12.

4. 11th Batch of Special Funding Projects of China Postdoctoral Science Foundation: “Research on short-term photovoltaic power prediction and energy storage capacity optimization based on feature selection”. 2019/01-2020/12.

5. 62nd Batch of General Projects of China Postdoctoral Science Foundation: “Research on short-term photovoltaic power prediction for complex weather”. 2018/01-2019/12.

6. Youth Project of Jiangxi Natural Science Foundation: “Research on short-term photovoltaic power prediction and relevant factors for complex weather”. 2018/01-2019/12.

7. Research Project of Postdoctoral Researchers in Jiangxi Province: “Short term photovoltaic power prediction and energy storage capacity optimization under the background of energy Internet”. 2018/01-2020/12.

8. Scientific Research Project of the Education Department of Jiangxi Province: “Online probability prediction of photovoltaic power considering complex uncertainty”. 2020/01-2021/12.

9. Scientific Research Project of the Education Department of Jiangxi Province: “The Application of adaptive feature extraction method in photovoltaic power prediction model”. 2017/01-2018/12.

Projects Participated:

1. Regional Project of the National Natural Science Foundation: “Research on resource assessment and short-term power prediction of grid-connected wind-solar power generation system”. 2018/01-2021/12.

2. Youth Project of Jiangxi Natural Science Foundation: “Research on dynamic adaptive wind speed prediction and wind energy resource evaluation based on data mining”. 2017/01-2019/12.

Papers:

1. He Jiang, Weihua Zheng, Liangqing Luo, Yao Dong, A two-stage minimax concave penalty based method in pruned Adaboost ensemble. Applied Soft Computing 2019; 83: 105674.

2. He Jiang, Yao Dong, Structural regularization in quadratic logistic regression model. Knowledge-Based Systems 2019; 163:842-857.

3. 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.

4. He Jiang, Sparse estimation based on square root nonconvex optimization in high dimensional data. Neurocomputing 2018; 282:122-135.

5. He Jiang, Model forecasting based on two-stage feature selection procedure using orthogonal greedy algorithm. Applied Soft Computing 2018; 63:110-123.

6. He Jiang, Yao Dong; Dimension reduction based on a penalized kernel support vector machine model. Knowledge-Based Systems 2017; 138:79-90.

7. 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.

8. 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.

9. 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.

10. He Jiang, Yao Dong，Ling 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.

11. 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.

12. 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 Energy Reviews 2015; 50:1304-1319.

13. 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.