姓 名：高飞

学 位：博 士

职 称：教 授

研究方向：分数阶系统、大数据分析、神经网络、机器学习、群智能算法等

联系方式：gaof@whut.edu.cn

电话：18971097697

个人主页：https://orcid.org/0000-0003-2266-7263

1.  简介

高飞 博士，武汉理工大学理学院数学系应用数学专业教授（2013.9-），居里夫人Marie-Curie Fellow，硕士生导师，归国留学博士后、博士后出站。从事涉及神经网络、机器学习、分数阶系统、群智能算法等领域的科学研究工作，并将它们应用于各种实际问题。

 2.  研究生招生

数学专业：应用数学、基础数学——机器学习、分数阶偏微分方程、大数据分析、神经网络、GPT与大语言模型、社交网络、无人机应用、混沌系统、随机微分方程、最优化理论与方法、

统计专业（学硕及专硕）：大数据分析、神经网络、机器学习、GPT与大语言模型、社交网络、无人机应用、混沌系统、随机微分方程、数理统计学相关

3.  概述

高飞博士在国内外重要学术期刊及高水平国际会议上发表论文60+篇，30+篇被三大检索收录。获得韩国政府BK21奖学金(2008.3-2009.3)和欧盟第七框架项目(2011.11-2012.10)资助，分别在韩国高等科学与技术研究院未来超越人类智能实验室、KAIST电气工程与计算机科学系、挪威科技大学NTNU电子与电信系从事计算智能及智能控制的博士后研究工作。

近年来参与国家自然科学基金重点项目（2014-2016）和面上项目（2013-2016）各一项；主持完成国家自然科学基金1项(2007)，中国博士后基金1项(2008-2009)，主持湖北省自然科学基金2项(2009-2011，2018-2019)。

国家精品课程<经济数学——高等数学B>主讲教师，自2002年以来进行高等数学A、B（含双语、纯英文教学）、微积分、概率统计、线性代数、复变函数与积分变换、最优化理论与方法、常微分方程、数值计算等课程的教学与研究。

4.  教育经历

2006.6毕业于武汉理工大学获博士学位；

2002.6毕业于武汉大学数学与统计学院应用数学专业，获理学硕士学位，获得“武汉大学数学学子奖”，并于2005年获得获湖北省优秀硕士论文；

1999.6在武汉大学数学与计算机科学学院获理学学士学位。

5.  科研与学术工作经历

2013/09 - 至今，武汉理工大学，理学院数学系，教授

2011/11–2012/10，挪威科技大学(NTNU)，信息科技与数学及电子工程学院， Marie Curie Fellow博士后(欧盟Marie Curie COFUND项目资助)

2008/03–2009/03，韩国科学技术研究院(KAIST)，电子系，博士后(韩国Brain Korea 21 Century项目资助)

2007/12 - 2013/09，武汉理工大学，理学院数学系，副教授

2006/11–2009/07，武汉理工大学，建筑学院，博士后

2004/11 - 2007/11，武汉理工大学，理学院数学系，讲师

6.  项目

1、湖北省自然科学基金项目，2014CFB865、分数阶超混沌的非Lyapunov重构研究、2015/01-2016/12、3万、结题、主持

2、国家自然科学基金重大研究计划项目，91324201、非常规突发事件下社会群体心理与行为变化规律和机制、2014/01-2016/12、175万、结题、参与

3、“Marie COFUND of the European Commission - ABCDE 项目，欧盟n°246016、Mathematical analysis on bio-inspired communication network theory、2011/11-2012/10、1万欧元、结题、主持

4、教育部(中国)留学科研启动基金项目，20111j0032、基于量子细菌趋化算法的非Lyapunov分析方法研究、2010/06-2011/12、3万、已结题、主持7.  论文（60+）

7.1    2024年迄今

[1]    Xu Y, Gao F. A novel higher-order Deffuant–Weisbuch networks model incorporating the Susceptible Infected Recovered framework[J]. Chaos, Solitons & Fractals, 2024, 182: 114778.

[2]    Xie X, Gao F. The Delayed Effect of Multiplicative Noise on the Blow-Up for a Class of Fractional Stochastic Differential Equations[J]. Fractal and Fractional, 2024, 8(3): 127.

7.2    2024年之前

[1]  ZHANG M, GAO F, YANG W, ZHANG H. Wildlife Object Detection Method Applying Segmentation Gradient Flow and Feature Dimensionality Reduction [J]. Electronics, 2023, 12(2).

[2]  ZHANG M, GAO F, YANG W, ZHANG H. Real-Time Target Detection System for Animals Based on Self-Attention Improvement and Feature Extraction Optimization [J]. Applied Sciences-Basel, 2023, 13(6).

[3]  GAO F, ZHAN H. Boundedness and exponential stabilization for time–space fractional parabolic–elliptic Keller–Segel model in higher dimensions [J]. Applied Mathematics Letters, 2023, 144: 108699.

[4]  GUO L, GAO F, ZHAN H. Existence, uniqueness and L8-bound for weak solutions of a time fractional Keller-Segel system [J]. Chaos Solitons & Fractals, 2022, 160.

[5]  ZHOU X, GAO F, FANG X, LAN Z. Improved Bat Algorithm for UAV Path Planning in Three-Dimensional Space [J]. Ieee Access, 2021, 9: 20100-16.

[6]  GAO F, LI X, LI W, ZHOU X. Stability analysis of a fractional-order novel hepatitis B virus model with immune delay based on Caputo-Fabrizio derivative [J]. Chaos Solitons & Fractals, 2021, 142.

[7]  GAO F, LI W-Q, TONG H-Q, LI X-L. Chaotic analysis of Atangana-Baleanu derivative fractional order Willis aneurysm system [J]. Chinese Physics B, 2019, 28(9).

[8]  ZHANG J, GAO F, CHEN Y, et al. Parameter Identification of Fractional-order Chaotic System Based on Chemical Reaction Optimization; proceedings of the 2nd International Conference on Management Engineering, Software Engineering and Service Sciences (ICMSS), Wuhan, PEOPLES R CHINA, F 2018, Jan 13-15, 2018 [C]. 2018.

[9]  GAO F, HU D-N, TONG H-Q, WANG C-M. Chaotic analysis of fractional Willis delayed aneurysm system [J]. Acta Physica Sinica, 2018, 67(15).

[10] MAO W, GAO F, DONG Y, LI W. A Novel Paradigm for Calculating Ramsey Number via Artificial Bee Colony Algorithm; proceedings of the 35th Chinese Control Conference (CCC), Chengdu, PEOPLES R CHINA, F 2016, Jul 27-29, 2016 [C]. 2016.

[11] GAO F, LI T, TONG H-Q, OU Z-L. Chaotic dynamics of the fractional Willis aneurysm system and its control [J]. Acta Physica Sinica, 2016, 65(23).

[12] GAO F, LEE T, CAO W-J, et al. Self-evolution of hyper fractional order chaos driven by a novel approach through genetic programming [J]. Expert Systems with Applications, 2016, 52: 1-15.

[13] GAO F, LEE X-J, FEI F-X, et al. Identification time-delayed fractional order chaos with functional extrema model via differential evolution [J]. Expert Systems with Applications, 2014, 41(4): 1601-8.

[14] GAO F, FEI F-X, LEE X-J, et al. Inversion mechanism with functional extrema model for identification incommensurate and hyper fractional chaos via differential evolution [J]. Expert Systems with Applications, 2014, 41(4): 1915-27.

[15] GAO F, LEE X-J, TONG H-Q, et al. Identification of Unknown Parameters and Orders via Cuckoo Search Oriented Statistically by Differential Evolution for Noncommensurate Fractional-Order Chaotic Systems [J]. Abstract and Applied Analysis, 2013.

[16] GAO F, LEE X-J, FEI F-X, et al. Parameter identification for Van Der Pol-Duffing oscillator by a novel artificial bee colony algorithm with differential evolution operators [J]. Applied Mathematics and Computation, 2013, 222: 132-44.

[17] GAO F, FEI F-X, TONG H-Q, et al. Bacterial Foraging Optimization Oriented by Atomized Feature Cloud Model Strategy; proceedings of the 32nd Chinese Control Conference (CCC), Xian, PEOPLES R CHINA, F 2013, Jul 26-28, 2013 [C]. 2013.

[18] GAO F, QI Y, BALASINGHAM I, et al. A Novel non-Lyapunov way for detecting uncertain parameters of chaos system with random noises [J]. Expert Systems with Applications, 2012, 39(2): 1779-83.

[19] GAO F, FEI F-X, XU Q, et al. A novel artificial bee colony algorithm with space contraction for unknown parameters identification and time-delays of chaotic systems [J]. Applied Mathematics and Computation, 2012, 219(2): 552-68.

[20] GAO F, FEI F-X, DENG Y-F, et al. A novel non-Lyapunov approach through artificial bee colony algorithm for detecting unstable periodic orbits with high orders [J]. Expert Systems with Applications, 2012, 39(16): 12389-97.

[21] XIAO J-Q, WU M, GAO F. Divergence points of self-similar measures satisfying the OSC [J]. Journal of Mathematical Analysis and Applications, 2011, 379(2): 834-41.

[22] GAO F, QI Y, YIN Q, XIAO J. Solving problems in chaos control though an differential evolution algorithm with region zooming; proceedings of the 2nd International Conference on Mechanical and Aerospace Engineering (ICMAE 2011), Bangkok, THAILAND, F 2012, Jul 29-31, 2011 [C]. 2012.

[23] GAO F, LEE J-J, LI Z, et al. Parameter estimation for chaotic system with initial random noises by particle swarm optimization [J]. Chaos Solitons & Fractals, 2009, 42(2): 1286-91.

[24] GAO F, GAO H, LI Z, et al. Detecting unstable periodic orbits of nonlinear mappings by a novel quantum-behaved particle swarm optimization non-Lyapunov way [J]. Chaos Solitons & Fractals, 2009, 42(4): 2450-63.

[25] GAO F, LI Z-Q, TONG H-Q. Parameters estimation online for Lorenz system by a novel quantum-behaved particle swarm optimization [J]. Chinese Physics B, 2008, 17(4): 1196-201.

[26] GAO F, LEE J-J, IEEE. A New Approach in Synchronization of Uncertain Chaos Systems Through Particle Swarm Optimization; proceedings of the 6th IEEE International Conference on Industrial Informatics, Daejeon, SOUTH KOREA, F 2008, Jul 13-16, 2008 [C]. 2008.

[27] GAO F, LEE J-J, IEEE. A New Approach in Discrete Chaos System Control by Differential Evolution Algorithm; proceedings of the 6th IEEE International Conference on Industrial Informatics, Daejeon, SOUTH KOREA, F 2008, Jul 13-16, 2008 [C]. 2008.

[28] GAO F, TONG H Q. Parameter estimation for chaotic system based on particle swarm optimization [J]. Acta Physica Sinica, 2006, 55(2): 577-82.

[29] GAO F, TONG H Q. A novel optimal PID tuning and on-line tuning based on particle swarm optimization; proceedings of the International Conference on Sensing, Computing and Automation, Chongqing, PEOPLES R CHINA, F Dec 2006, May 08-11, 2006 [C]. 2006.

[30] GAO F, TONG H, IEEE. Control a novel discrete chaotic system through Particle Swarm Optimization; proceedings of the 6th World Congress on Intelligent Control and Automation, Dalian, PEOPLES R CHINA, F 2006, Jun 21-23, 2006 [C]. 2006.

[31] GAO F, TONG H. UEAS: A novel united evolutionary algorithm scheme [M]//KING I, WANG J, CHAN L, WANG D L. Neural Information Processing, Pt 3, Proceedings. 2006: 772-80.

[32] GAO F, TONG H. Differential evolution: An efficient method in optimal PID tuning and on-line tuning [J]. Dynamics of Continuous Discrete and Impulsive Systems-Series B-Applications & Algorithms, 2006, 13: 785-9.

[33] GAO F, TONG H. Particle swarm optimization: An efficient method for tracing periodic orbits and controlling chaos [J]. Dynamics of Continuous Discrete and Impulsive Systems-Series B-Applications & Algorithms, 2006, 13: 780-4.