薛羽，男，博士，南京信息工程大學教授，博導/碩導。
基本介紹
- 中文名：薛羽
- 學位/學歷：博士
- 職業：教師
- 專業方向：Application Technology of Computer
- 任職院校：南京信息工程大學
個人經歷,主講課程,研究方向,學術成果,
個人經歷
Aug. 2016-Now
Associate Professor, Professor, School of Computer and Software, Nanjing University of Information Science and Technology, China
Superviser of graduate students, superviser of Ph. D students
Jul. 2013-Aug. 2016
Lecturer, School of Computer and Software, Nanjing University of Information Science and Technology, China
Oct. 2017-Nov. 2018
Research Scholar, Department of Computer Science and Engineering, Michigan State University, United States
Aug. 2016-Aug. 2017
Visiting Scholar, School of Engineering and Computer Science, Victoria University of Wellington, New Zealand
學術與社會兼職
《IEEE Transactions on Evolutionary Computation》
《IEEE Transactions on Cybernetics》
《IEEE Transactions on Fuzzy Systems》
《IEEE Transactions on Emerging Topics in Computing》
《IEEE Transactions on Computational Intelligence and AI in Games》
《Computer Methods and Programs in Biomedicine》
《Swarm and Evolutionary Computation》
《Memetic Computing》
《Applied Soft Computing》
《Natural Computing》
《IEEE ACCESS》
《Soft Computing》
《Artificial Intelligence Review》
《Knowledge-Based Systems》
《Information Science》
《IET Image Processing》
《International Journal of Machine Learning and Cybernetics》
《Journal of Internet Technology》
《Applied Mathematics and Computation》
《International Journal of Systems, Control and Communications》
《Journal of Industrial and Management Optimization》
《International Journal of Swarm Intelligence Research》
《Computer Network》
《Egyptian Informatics Journal》
《Sadhana》
《Applied Thermal Engineering》
《Journal of King Saud University - Computer and Information Sciences》
《Scientific Report》
《Concurrency and Computation: Practice and Experience》
《Fuzzy Optimization and Decision Making》
《China Communication》
等期刊審稿人。
主講課程
機器學習(Machine Learning)、離散數學(Discrete Mathematics)， 作業系統（Operating System）
研究方向
Intelligent Computing
Machine Learning and Data Mining
學術成果
Projects:
(1) 國家自然科學基金-面上項目(項目號：61876089；2019-2022；主持)
(2) 國家自然科學基金-青年基金(項目號：61403206；2015-2017；主持)
(3) 江蘇省自然科學基金-青年基金(項目號：BK20141005；2014-2016；主持)
(4) 江蘇省高校自然科學研究項目資助(項目號：14KJB520025；2014-2015；主持)
(5) 南京信息工程大學科研啟動費(項目號：2013x034；2013-2014；主持)
(6) 江蘇省普通高校研究生科研創新項目（項目號：CXLX11_0203；2011-2013；主持）
Published papers:
[1] Y. Xue, B. Xue, and M. Zhang, “Self-adaptive particle swarm optimization for large-scale feature selection in classification,” ACM Transactions on Knowledge Discovery from Data, vol. 13, no. 5, pp. 1-28, 2019.
The codes can be obtained_02-MatlabCodes-EvolutionaryFeatureSelectionForClassificationrar
[2] Y. Xue, T. Tang, W. Pang, and A. X. Liu, “Self-adaptive parameter and strategy based particle swarm optimization for large-scale feature selection problems with multiple classifiers,” Applied Soft Computing, pp. 106031, 2019,
[3] Y. Xue, T. Tang, and A. X. Liu, “Large-scale feedforward neural network optimization by a self-adaptive strategy and parameter based particle swarm optimization,” IEEE Access, vol. 7, no. 7, pp. 52473-52483, 2019.
[4] Y. Xue, B. P. Zhao, T. H. Ma, and A. X. Liu, “An evolutionary classification method based on fireworks algorithm,” International Journal of Bio-Inspired Computation, vol. 11, no. 3, pp. 149-158, 2018.
[5] Y. Xue, B. Zhao, T. Ma, and W. Pang, “A Self-adaptive fireworks algorithm for classification problems,” IEEE Access, vol. 06, no. 01, pp. 44406-44416, 2018.
[6] Y. Xue, J. M. Jiang, B. P. Zhao, and T. H. Ma, “A self-adaptive artificial bee colony algorithm based on global best for global optimization,” Soft Computing, vol. 22, no. 9, pp. 2935-2952, May, 2018.
The codes can be obtained
該論文入選2018年中國百篇最具影響國際學術論文,100篇論文選自2018年發表在24個學科的31.59萬篇論文。
[7] Y. Xue, J. M. Jiang, T. H. Ma, J. F. Liu, and W. Pang, “A self-adaptive artificial bee colony algorithm with symmetry initialization,” Journal of Internet Technology, vol. 19, no. 5, pp. 1347-1362, Sep, 2018.
[8] Y. Xue, W. W. Jia, X. J. Zhao, and W. Pang, “An evolutionary computation based feature selection method for intrusion detection,” Security and Communication Networks, vol. 2018, pp. 1-10, 2018, 2018.
[9] J. M. Jiang, Y. Xue, and T. H. Ma, “Improved artificial bee colony algorithm with differential strategy for the large scale global optimization problem,” International Journal of Computational Science and Engineering, vol. 16, no. 01, pp. 73-84, 2018.
[10] Y. Xue, J. M. Jiang, B. Xue, and M. J. Zhang, A classification method based on self-adaptive artificial bee colony, New York: IEEE, 2017.
[11] B. Zhao, T. Ma, and Y. Xue, “Performance analysis for clustering algorithms,” International Journal of Computing Science and Mathematics, vol. 7, no. 5, pp. 485, 2016.
[12] Y. Xue, B. P. Zhao, and T. H. Ma, “Classification based on fireworks algorithm,” in Bio-Inspired Computing-Theories and Applications, 2016, pp. 35-40.
[13] Y. Xue, T. Tang, and T. Ma, "Classification based on brain storm optimization algorithm." pp. 371-376.
[14] Y. Xue, J. M. Jiang, T. H. Ma, and C. Li, “The performance research of artificial bee colony algorithm on the large scale global optimisation problems,” International Journal of Wireless and Mobile Computing, vol. 9, no. 3, pp. 300-305, 2015.
[15] 薛羽, 莊毅, 許斌, and 張友益, “基於自適應學習群體搜尋技術的集成進化算法,” 系統工程理論與實踐, vol. 34, no. 02, pp. 458-465, 2014.
[16] 薛羽, 莊毅, 顧晶晶, 常相茂, and 王洲, “自適應離散差分進化算法策略的選擇,” 軟體學報, vol. 25, no. 05, pp. 984-996, 2014.
[17] Y. Xue, S. Zhong, Y. Zhuang, and B. Xu, “An ensemble algorithm with self-adaptive learning techniques for high-dimensional numerical optimization,” Applied Mathematics and Computation, vol. 231, pp. 329-346, Mar, 2014.
[18] Y. Xue, S. Zhong, T. Ma, and J. Cao, “A hybrid evolutionary algorithm for numerical optimization problem,” Intelligent Automation & Soft Computing, vol. 21, no. 4, pp. 473-490, Oct, 2014.
[19] Y. Xue, X. M. Chang, S. M. Zhong, and Y. Zhuang, “An efficient energy hole alleviating algorithm for wireless sensor networks,” IEEE Transactions on Consumer Electronics, vol. 60, no. 3, pp. 347-355, Aug, 2014.
[20] 薛羽, 莊毅, 孟新, and 張友益, “自適應學習集成最佳化算法及矩陣特徵值求解,” 計算機研究與發展, vol. 50, no. 07, pp. 1435-1443, 2013.
[21] Y. Xue, Y. Zhuang, T. Q. Ni, J. Ouyang, and Z. Wang, “Enhanced self-adaptive evolutionary algorithm for numerical optimization,” Journal of Systems Engineering and Electronics, vol. 23, no. 6, pp. 921-928, Dec, 2012.
