Aug. 2016-Now

Projects:(1) 国家自然科学基金-面上项目(项目号：61876089；2019-2022；主持)(2) 国家自然科学基金-青年基金(项目号：61403206；2015-2017；主持)(3) 江苏省自然科学基金-青年基金(项目号：BK20141005；2014-2016；主持)(4) 江苏省高校自然科学研究项目资助(项目号：14KJB520025；2014-2015；主持)(5) 南京信息工程大学科研启动费(项目号：2013x034；2013-2014；主持)(6) 江苏省普通高校研究生科研创新项目（项目号：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 inclassification,” ACM Transactions on Knowledge Discovery from Data, vol. 13,no. 5, pp. 1-28, 2019. The codes can be obtained @https://www.researchgate.net/publication/335788589_02-MatlabCodes-EvolutionaryFeatureSelectionForClassificationrar[2] Y. Xue, T. Tang, W. Pang, and A. X.Liu, “Self-adaptive parameter and strategy based particle swarm optimizationfor large-scale feature selection problems with multiple classifiers,” AppliedSoft Computing, pp. 106031, 2019, doi:https://doi.org/10.1016/j.asoc.2019.106031.[3] Y. Xue, T. Tang, and A. X. Liu,“Large-scale feedforward neural network optimization by a self-adaptivestrategy 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, “ASelf-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 bestfor global optimization,” Soft Computing, vol. 22, no. 9, pp. 2935-2952,

May,2018.The codes can be obtained @https://www.researchgate.net/publication/315515802_SABCGB该论文入选2018年中国百篇最具影响国际学术论文,100篇论文选自2018年发表在24个学科的31.59万篇论文。 官网对2019中国科技论文统计结果的相关报道：http://www.gov.cn/shuju/2019-11/20/content_5453698.htmhttp://gz.people.com.cn/n2/2019/1126/c358164-33576886.htmlhttp://www.miit.gov.cn/n1146290/n1146402/n1146445/c7542424/content.html[7] Y. Xue, J. M. Jiang, T. H. Ma, J. F.Liu, and W. Pang, “A self-adaptive artificial bee colony algorithm withsymmetry 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 intrusiondetection,” 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 thelarge scale global optimization problem,” International Journal ofComputational 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 ofComputing 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-InspiredComputing-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 largescale global optimisation problems,” International Journal of Wireless andMobile Computing, vol. 9, no. 3, pp. 300-305, 2015.[15] 薛羽, 庄毅, 许斌, and 张友益, “基于自适应学习群体搜索技术的集成进化算法,” 系统工程理论与实践, vol. 34, no. 02, pp. 458-465,2014.[16] 薛羽, 庄毅, 顾晶晶, 常相茂, and 王洲, “自适应离散差分进化算法策略的选择,” 软件学报, 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 forhigh-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, andY. Zhuang, “An efficient energy hole alleviating algorithm for wireless sensornetworks,” IEEE Transactions on Consumer Electronics, vol. 60, no. 3, pp.347-355, Aug, 2014.[20] 薛羽, 庄毅, 孟新, and 张友益, “自适应学习集成优化算法及矩阵特征值求解,” 计算机研究与发展, 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 fornumerical optimization,” Journal of Systems Engineering and Electronics, vol.23, no. 6, pp. 921-928, Dec, 2012.