黄兆可
团队名称：智能控制与优化决策
团队介绍：致力于不确定优化、可解释机器学习和多目标优化与决策等方法的基础理论研究，同时从事流程工业智能优化制造、综合能源系统、智能交通、智慧医疗等领域的应用研究。
团队成员介绍：
15级博士生（已博士毕业）, 主要从事不平衡数据处理、双层规划、数据挖掘等方面的研究, 目前已发表的学术论文有：
[1] 黄兆可, 阳春华, 周晓君, 桂卫华. A novel cognitively-inspired state transition algorithm for solving the linear bi-level programming problem[J]. Cognitive Computation, 2018, DOI: 10.1007/s12559-018-9561-1.
[2] 黄兆可, 阳春华, 周晓君等. A hybrid feature selection method based on binary state transition algorithm and ReliefF[J],IEEE Journal of Biomedical and Health Informatics, DOI: 10.1109/JBHI.2018.2872811
[3] 黄兆可，阳春华, 周晓君等. Energy consumption forecasting for the nonferrous metallurgy industry using hybrid support vector regression with an adaptive state transition algorithm[J], Cognitive Computation, https://doi.org/10.1007/s12559-019-09644-0
[4] 黄兆可，阳春华，陈晓方等. Adaptive over-sampling method for classification with application to imbalanced datasets in aluminum electrolysis[J], Neural Computing and Applications, https://doi.org/10.1007/s00521-019-04208-7
[5] 黄兆可，阳春华，陈晓方，周晓君等. Functional deep echo state network improved by a bi-level optimization approach for multivariate time series classification[J]. Applied Soft Computing, accepted.