[1] Qiang He, Meng Li, Lianzhi Huo, Linlin Chen, Learning to detect extreme objects for remote sensing images, International Journal of Machine Learning and Cybernetics, 2024, 15(7), pp.2719–2736.

[2] Qiang He, Guanqun Wang, Hengyou Wang, Linlin Chen, Multivariate time-series anomaly detection via temporal convolutional and graph attention networks, Journal of Intelligent & Fuzzy Systems, 2023, 44(4), 5953–5962.

[3] Qiang He, Guanqun Wang, Lianzhi Huo, Hengyou Wang, Changlun Zhang, ACAM-AD: Autocorrelation and attention mechanism-based anomaly detection in multivariate time series, Journal of Intelligent & Fuzzy Systems, 2023, 44(6) , pp.9039-9051.

[4] 李静，何强，张长伦，王恒友，基于全局注意力的室内人数统计模型，计算机工程与科学，第44卷，第3期，471-478，2022年3月.

[5] Qiang He, Qingshuo Zhang, Hengyou Wang, Changlun Zhang, Local Similarity Based Fuzzy Multiple Kernel One-class Support Vector Machine, COMPLEXITY, 2020, DOI: 10.1155/2020/8853277

[6] Qiang He, Yujing Zheng, Changlun Zhang, Hengyou Wang, MTAD-TF: Multivariate Time Series Anomaly Detection Using the Combination of Temporal Pattern and Feature Pattern, COMPLEXITY, 2020, DOI: 10.1155/2020/8846608

[7] 郑育靖，何强，张长伦，王恒友，基于GRU-Attention的无监督多变量时间序列异常检测，山西大学学报(自然科学版)，第43卷，第4期，754-764，2020年12月

[8] 张庆朔，何强，张长伦，王恒友, 模糊多核一类支持向量机. 北京建筑大学学报, 第36卷, 第1期, 82-90, 2020年3月

[9] 何强，张娇阳．核对齐多核模糊支持向量机．智能系统学报, 第14卷，第6期 , 1163-1169，2019年11月

[10] Qiang He, Qingshuo Zhang, Kernel-target Alignment Based Multiple Kernel One-class Support Vector Machine, 2019 IEEE International Conference on Systems, Man and Cybernetics, Bari, Italy, October 6-9, 2019.

[11] Changzhong Wang, Qiang He, Mingwen Shao, Qinghua Hu. Feature selection based on maximal neighborhood discernibility. International Journal of Machine Learning and Cybernetics. 2018， 9 (11) , pp.1929-1940

[12] Changzhong Wang, Qiang He, Degang Chen, Qinghua Hu. A novel method for attribute reduction of covering decision systems. Information Sciences, 2014, 254, pp181-196

[13] Qiang He, Zongxia Xie, Qinghua Hu, Congxin Wu, Neighborhood based sample and feature selection for SVM classification learning. Neurocomputing, 2011， 74(10), pp. 1585-1594

[14] Qiang He, Congxin Wu, Membership Evaluation and Feature Selection for Fuzzy Support Vector Machine Based on Fuzzy Rough Sets. Soft Computing. 2011, 15(6), pp. 1105-1114

[15] Qiang He, Congxin Wu, Degang Chen, Suyun Zhao, Fuzzy rough set based attribute reduction for information systems using fuzzy decisions. Knowledge-based Systems. 2011, 24(5), pp. 689–696

[16] Qiang He, Congxin Wu, Separating theorem of samples in Banach space for support vector machine learning. International Journal of Machine Learning and Cybernetics, 2011, 2(1), pp. 49-54

[17] Qiang He, Hongliang Li, Separation theorem and maximal margin classification for fuzzy number spaces, 2011 International Conference on Machine Learning and Cybernetics, 2011, PP. 278 – 281

[18] Degang Chen, Sam Kwong, Qiang He, Hui Wang, Geometrical interpretation and applications of membership functions with fuzzy rough sets, Fuzzy Sets and Systems, 2012, 193, pp. 122–135

[19] Degang Chen, Qiang He, Xizhao Wang, FRSVMs: Fuzzy rough set based support vector machines, Fuzzy Sets and Systems, 2010, 161(4), pp. 596-607

[20] Junfen Chen, Qiang He, Yan Li, Different Types Classifiers Combination Based on the Choquet Integrals in Classification, The 2010 International Conference on Systems, Man and Cybernetics, 2010, pp. 4056 - 406