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蒋锋

发布者：刘巍发布时间：2017-05-13浏览次数：15178

姓名：蒋锋

性别：男

籍贯：湖北

民族：汉

所在系：数理与金融统计学系

教研室：

是否博导：是

是否硕导：是

职称：教授

现任职务：系主任、应用统计专业硕士大数据导师组组长

电子邮箱：fjiang@zuel.edu.cn


讲授课程：

1)本科课程：

数据科学专题、机器学习、非参数统计学、大数据时代下数据化决策与统计思维、多元统计分析、概率论、数理统计学、时间序列分析、Python数据分析等；  

2)硕士课程：

论文写作与学术规范、机器学习、统计计算与软件、大数据及其应用、应用统计案例分析、应用多元统计分析、大数据与数据思维等；

3)博士课程：

Topics in Statistics、应用统计学前沿专题、统计计算与模拟（数值计算与统计模拟）、一级学科经典文献（统计学）、量化投资等


研究方向：

统计机器学习及应用、群智能优化与计算、神经网络及应用、金融模型与风险控制、大数据建模理论方法及应用。


社会职务：

全国工业统计学教学研究会理事，中国统计教育学会理事，中国技术经济学会金融科技委员会常务理事，中国现场统计研究会经济与金融统计分会理事等


个人简历(教育背景、工作经历等)：

教育经历：

  1.  2008.09-2011.06华中科技大学系统分析与集成理学博士

  2.  2002.09-2005.07 华中师范大学概率论与数理统计理学硕士

  3.  1998.09-2002.07 三峡大学数学理学学士

工作经历：

  1.  2011．07-至今 中南财经政法大学统计与数学学院

  2.  2017.07-2017.08 澳大利亚Monash大学数学科学系访问学者

  3.  2015.08-2016.08 澳大利亚Monash大学数学科学系访问学者

  4.  2011.10-2013.10 华中科技大学控制科学与工程博士后

  5.  2005.07-2008.08 华北电力大学理学院讲师


教学与科研项目：

  1. 主持国家自然科学基金项目面上项目（61773401，2018-2021）

  2. 主持湖北省重点实验室项目（2021）

  3. 主持湖北省社科基金一般项目（2020209,2020）

  4. 主持武汉市社科基金后期资助项目（2019021，2020）

  5. 主持湖北金融统计学会重点课题项目（2019、2020）

  6. 主持完成湖北省社科项目一般项目（2017132，2018）

  7. 主持完成湖北省教育厅人文社科项目（17G024，2017-2018）

  8. 主持完成国家自然科学基金项目青年项目（61304067，2014-2016）

  9. 主持完成湖北省自然科学基金项目（2013CFB443，2013-2015）

  10. 主持教育部产学合作协同育人项目 (201901104037，2019-2020)

  11. 主持中央高校教育教学改革项目（2018-2020，结项：优秀）


专著/教材：

1）蒋锋.神经网络及其在数据科学中的应用.中国财政经济出版社， 2019.

2）蒋锋，随机系统数值方法的动力学分析及应用，科学出版社，2016.

3）蒋锋、姜旭初编著，Python数据分析，中国财政经济出版社，2021

4）专利：基于股票大数据的统计分析虚拟仿真系统V1.0（2020）


近年科研论文（英/中）代表作：

  1. Feng Jiang, Y Qiao, X Jiang, T Tian, MultiStep Ahead Forecasting for Hourly PM10 and PM2.5 Based on Two-Stage Decomposition Embedded Sample Entropy and Group Teacher Optimization Algorithm, Atmosphere 2021, 12: 1-18

  2. Feng Jiang，J He, Tian T H. A clustering-based ensemble approach with improved pigeon-inspired optimization and extreme learning machine for air quality prediction. Applied Soft Computing, 2019, 85: 105827.  

  3. Feng Jiang，J He，Z Zeng，Pigeon-inspired optimization and extreme learning machine via wavelet packet analysis for predicting bulk commodity futures prices. Science China Information Sciences, 2019, 62(7): 70204

  4. X Jiang, Feng Jiang, B Zhang, Operational modal analysis of a nonlinear oscillation system under a harmonic excitation, 2020, J Mechanical Engineering Science, 0(0) 1–14

  5. X Jiang, Feng Jiang. Operational modal analysis using symbolic regression for a nonlinear vibration system. Journal of Low Frequency Noise Vibration and Active Control, 2020, 0(0): 1-15.

  6. X Jiang, Feng Jiang. Optimal strain sensors placement to analyze the modal parameters of the sorting arm, Journal of Vibroengineering, 2020, 22(1):145-155.

  7. Y Song, Feng Jiang. Quasi-synchronization of stochastic memristor-based neural networks with mixed delays and parameter mismatches，Neural Computing and Applications,  2020, 32(5):4615-4628.

  8. Feng Jiang， Jiawei Yang，Ultra-short-term wind power forecast using ensemble learning and Elephant Herd optimization algorithm， ICICIP2019

  9. Feng Jiang，Yunfei Zhang, Electric Load Forecasting Based on CEEMDAN and LSSVM Optimized by Cuckoo Search Algorithm, EI2 2019

  10. Feng Jiang, jointly with Guodong Zhang,Exponential stability criteria for delayed second-ordermemristive neural       networks, Neurocomputing，315（2018）439-446

  11. Feng Jiang, jointly with Yinfang Song, Zhigang Zeng, Quasi-synchronization of stochastic memristor-based neural networks with mixed delays and parameter mismatches, Neural Computing and Applications, 2018.

  12. Feng Jiang, jointly with Jiaqi He, H Yang, Hybrid genetic algorithm and support vector machine performance in public fiscal revenue pridiction, CCC2018.

  13. Feng Jiang,jointly with Zijun Peng, Jiaqi He, Short-term load forecasting based on support vector regression with improved grey wolf optimizer, ICACI, 2018

  14. Feng Jiang, jointly with Jiaqi He, Zijun Peng, Short-term wind power forecasting based on BP neural network with improved ant lion optimizer, CCC2018

  15. Feng Jiang, jointly with W. Wu, Z. Peng, A simi-parametric quantile regression random forest approach for evaluating muti-period value at risk, Proceeding of the Chinese Control Conf, 2017:5642-5646

  16. Feng Jiang, Hua Yang, Tianhai Tian, Property and numerical simulation of the Ait-Sahalia-Rho model with nonlinear growth conditions, Discrete and Continuous Dynamical Systems Series B, 2017(22)

  17. Q Zhu, Feng Jiang, H. Wang, B. Wang, Comment on Stability analysis of stochastic differential equations with Markovian switching，Systems & Control Letters, 2017: 102-103

  18. Feng Jiang,Wenjun Wu,Hybrid Genetic Algorithm and Support Vector Regression Performance in CNY Exchange Rate Prediction，ESM, 2016

  19. Feng Jiang, Hua Yang, Yi Shen, Stability of Second-order  Stochastic Neutral Partial Functional Differential Equations Driven by Impulsive Noises，中国科学（信息科学）， 2016（11），SCI

  20. Hua Yang, Jianguo Liu, Feng Jiang, Stability Analysis for a Class of Jump-Diffusion Systems with Parameter，: IEEE 7th International Conference on Intelligent Control and Information Processing (ICICIP), 2016: 217-222

  21. H. Yang, J. Liu, Feng Jiang, Stability analysis for a class of jump-diffusion systems with parameter, 7th International Conference on Intelligent Control and Information Processing, ICICIP 2016: 217-222

  22. Feng Jiang, Wenjun Wu, Hybrid Particle Swarm Optimization and Support Vector Regression Performance in Exchange Rate Prediction，International Journal of Economics and Business Administration, Vol. 2, No. 5, Nov. 2016, pp. 59-64.   

  23. Feng Jiang, Yi Shen，Exponential Stability  of  Stochastic Evolution Jump-Diffusions Driven by Impulses,  CCC2016, vol. 2016-August, 2016, 1723-1728.

  24. Y. Song，W. Sun, F. Jiang, Mean-square exponential input-to-state stability for neutral stochastic neural networks with mixed delays, Neurocomputing,  2016, 205(C):195-203

  25. Feng Jiang, H. Yang, T. Tian, Stability analysis for second-order stochastic neutral partial functional systems subject to infinite delays and impulses, Adv Differ Equ (2016) 2016: 224.

  26. Feng Jiang, H. Yang, Y. Shen, A note on  exponential stability for second-order neutral stochastic  partial  differential equations with infinite delays in the presence of impulses, Applied Mathematics and Computation, vol. 287-288, September, 2016, 125-133

  27. Hua Yang ; Jianguo Liu; Feng Jiang，Exponential stability of nonlinear dynamic systems with delay,  Proceedings of 6th International Conference on Intelligent Control and Information Processing, ICICIP 2015, 2016: 237-240

  28. Yang, Hua; Jiang, Feng，Almost Sure Exponential Stability of Neutral Stochastic Hybrid Evolution Systems，3rd International Conference on Management Science, Education Technology, Arts, Social Science and Economics, 2015(21-22): 901-905

  29. W.Xie, Q. Zhu, Feng Jiang, Exponential stability of stochastic neural networks with leakage delays and expectations in the coefficients, Neurocomputing, 2016 (173): 1268-1275

  30. S. Senthilraj, R. Raja, Feng Jiang, Q. Zhu, R. Samidurai, New delay-interval-dependent stability analysis of neutral type BAM neural networks with successive time delay components, Neurocomputing,2016(171): 1265–1280

  31. Feng Jiang, Hua Yang, Xinquan Zhao, On the asymptotic stability of a class of jump-diffusions of neutral type with impulses, Journal of Inequalities and Applications, 2013, 2013:561

  32. S. Xiong, Q. Zhu, Feng Jiang, Globally asymptotic stabilization of stochastic nonlinear systems in strict-feedback form, Journal of the Franklin Institute, 2015(352): 5106-5121

  33. H. Yang, J. Liu, Feng Jiang, Exponential Stability of Jump-Diffusion Systems with Neutral Term and Impulses, Math. Probl. Eng., Mathematical Problems in Engineering, Volume 2015 (2015), Article ID 192083

  34. H.Yang, J. Liu, Feng Jiang, Exponentially Attractive Set and Positive Invariant Set of a Class of Chaos  Systems,   International Conference on Sustainable Energy and Environment Protection (ICSEEP) ，2015: 601-605

  35. Q. Wu, Feng Jiang, T. Tian, Sensitivity and Robustness Analysis for Stochastic Model of Nanog Gene Regulatory Network, International Journal of Bifurcation and Chaos, 2015, 25(7): 1540009

  36. 蒋锋，何佳琪，曾志刚，田天海，基于分解-优化-集成学习方法的电价预测，中国科学：信息科学，2018，48(10),1300-1315

  37. 蒋锋，乔雅倩，基于样本熵和优化极限学习机的PM2.5浓度预测，统计与决策，2021

  38. 蒋锋，杨嘉伟，MOEA/D多目标集成学习的大豆期货价格预测，统计与决策，2021

  39. 蒋锋，杨嘉伟，基于多目标优化集成学习的短期太阳辐射预测，云南大学学报自然科学版，2021

  40. 刘寅, 张弛, 蒋锋. 多元零浮动负二项分布模型在美国老龄化研究中的应用，数理统计与管理, 2020(3):406-416.

  41. 蒋锋，彭紫君，基于混沌PSO优化BP神经网络的碳价预测， 统计与信息论坛，2018（5）

  42. 蒋锋，张婷，周琰玲，基于Lasso-GRNN神经网络模型的地方财政收入预测，统计与决策，2018（19）