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  1. Zhao Wang, Maoguo Gong, Peng Li, Fei Xie, Mingyang Zhang. A Bi-Level Gene-Based Multiobjective Memetic Algorithm for Passive Localization System Deployment Optimization. IEEE Transactions on Evolutionary Computation, 2022, early access.(中科院分区一区TOP期刊,行业顶刊,一类贡献度,IF 11.554)
  2. Zhao Wang, Maoguo Gong. Dynamic Deployment Optimization of Near Space Communication System Using a Novel Estimation of Distribution Algorithm. Applied Soft Computing, Vol. 78, 2019: 569-582.  (中科院分区一区TOP期刊,一类贡献度)
  3. Zhao Wang, Maoguo Gong, Peng Li, Jie Gu, Weidong Tian. A Hypervolume Distribution Entropy Guided Multiobjective Evolutionary Algorithm Based on Decomposition. Applied Soft Computing, Vol.116, 2022. (中科院分区一区TOP期刊,一类贡献度)
  4. Zhao Wang, Fenlong Jiang, Tongfei Liu, Fei Xie, Peng Li. Attention-Based Spatial and Spectral Network with PCA-Guided Self-Supervised Feature Extraction for Change Detection in Hyperspectral Images. Remote Sensing, Vol. 13 no. 23, 2021: 4927.
  5. Zhao Wang, Jianzhao Li, Yiting Liu, Fei Xie, Peng Li. An Adaptive Surrogate-Assisted Endmember Extraction Framework Based on Intelligent Optimization Algorithms for Hyperspectral Remote Sensing Images. Remote Sensing, vol. 14, no. 4, 2022. 
  6. Maoguo Gong, Zhao Wang, Zexuan Zhu, Licheng Jiao. A Similarity-Based Multiobjective Evolutionary Algorithm for Deployment Optimization of Near Space Communication System. IEEE Transactions on Evolutionary Computation, Vol. 21, No. 6, 2016: 878-897. (中科院分区一区TOP期刊,行业顶刊,一类贡献度,IF 11.554)
  7. Zhao Wang, Maoguo Gong, Yu Lei, Shanfeng Wang, Linzhi Su. A Memetic Algorithm based on MOEA/D for Near Space Communication System Deployment Optimization on Tide User Model. IEEE Congress on Evolutionary Computation, 2016: 3614-3621.
  8. Zhao Wang, Maoguo Gong, Qing Cai, Lijia Ma, Licheng Jiao. Deployment Optimization of Near Space Airships based on MOEA/D with Local Search. IEEE Congress on Evolutionary Computation, 2014: 2345-2352.
  9. Zhao Wang, Maoguo Gong, Tian Xie. Decision Variable Analysis based on Distributed Computing. International Conference on Bio-Inspired Computing: Theories and Applications, 2017: 447-455.
  10. Zhengyang Yu, Jianlong Tang, Zhao Wang. GCPS: A CNN Performance Evaluation Criterion for Radar Signal Intrapulse Modulation Recognition. IEEE Communications Letters, Early Access.
  11. Xiaolong Hui, Bin Wu, Peng Li, Chao Hou, Zhao Wang. Highly Contaminated Work Mode Identification of Phased Array Radar Using Deep Learning Method. 2020 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2020.
  12. Jiayue Wu, Bin Wu, Haonan Niu, Congcong Ma, Zhao Wang, Peng Li. A Novel Support Vector Machine Based Radar Individual Recognition Algorithm Under Inconsistent Noise Condition. 2020 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2020.
  13. Zehuan Jing, Bin Wu, Peng Li, Rui Yang, Jingyi Li, Zhao Wang. A Novel Variational Autoencoder based Radar Signal Reconstruction Algorithm Using Polluted Data. 2020 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2020.
  14. Linzhi Su, Jiao Shi, Puzhao Zhang, Zhao Wang, Maoguo Gong. Detecting Multiple Changes from Multi-Temporal Images by Using Stacked Denosing Autoencoder Based Change Vector Analysis. International Joint Conference on Neural Networks. 2016: 1269-1276
  15. Jianan Yan, Shasha Ruan, Qing Cai, Jiao Shi, Zhao Wang, Maoguo Gong. A Novel Bi-Objective Model with Particle Swarm Optimizer for Structural Balance Analytics in Social Networks. IEEE Congress on Evolutionary Computation, 2016: 728-735
  16. Tian Xie, Maoguo Gong, Zedong Tang, Yu Lei, Jia Liu, Zhao Wang. Enhancing Evolutionary Multifactorial Optimization based on Particle Swarm Optimization. IEEE Congress on Evolutionary Computation, 2016: 1658-1665
  17. Shanfeng Wang, Maoguo Gong, Bo Shen, Zhao Wang, Qing Cai, Licheng Jiao. Deep Community Detection based on Memetic Algorithm. IEEE Congress on Evolutionary Computation, 2015: 648-655
  18. Jingjing Ma, Yu Lei, Zhao Wang, Licheng Jiao, Ruochen Liu. A Memetic Algorithm based on Immune Multi-Objective Optimization for Flexible Job-shop Scheduling Problems. IEEE Congress on Evolutionary Computation, 2014:58-65