1.         Dun Liu, Xiuyi Jia, Huaxiong Li, Fan Min, Hong Yu. Three-Way Decisions and Big Data Analysis, Science Press, Beijing, 2020.

刘盾, 贾修一, 李华雄, 闵帆, 于洪. 三支决策与大数据分析. 科学出版社, 北京, 2020. ISBN: 978-7-03-065580-6

2.         Hong Yu, Guoyin Wang, Tianrui Li, Jiye Liang, Duoqian Maio (Eds.). Three-Way Decisions: Methods and Practices of Complex Problem Solving, Sience Press, Beijing, 2015.

于洪, 王国胤, 李天瑞, 梁吉业, 苗夺谦, 姚一豫编著. 三支决策: 复杂问题求解方法与实践. 科学出版社, 北京, 2015.

3.         Guoyin Wang, Qun Liu, Hong Yu, Xianhua Zeng (Eds.). Big Data Mining and Application. Tsinghua University Press, Beijing, 2017.

王国胤，刘群，于洪，曾宪华编著. 大数据挖掘及应用. 清华大学出版社, 北京, 2017.

4.         Hong Yu, Ting Su, Guoyin Wang. Three-way Decision Clustering Method for Incomplete Data. (chapter 8), in Yanping Zhang, Yiyu Yao, Duoqian Miao, Guoyin Wang, Jiye Liang, Tianrui Li, Weizhi Wu, Shu Zhao (Eds.), Historical Perspectives on and Future of Granlar Computing, Quotient Spaces, and Three-way Decisions, Sience Press, Beijing, 2017.05.

于洪, 苏婷, 王国胤. 面向不完备数据的三支决策聚类方法. 张燕平, 姚一豫, 苗夺谦, 王国胤, 梁吉业, 李天瑞, 吴伟志, 赵姝编著. 粒计算、商空间及三支决策的回顾与发展. 科学出版社, 北京. 2017(2017年05月,第8章).

5.         Hong Yu, Ying Wang, Guoyin Wang. Granular Computing Based on Three-way Decision. (Chapter 11), in Dun Liu, Tianrui Li, Duoqian Miao, Guoyin Wang, Jiye Liang (Eds.). Three-way Decisions and Granular Computing. Science Press, Beijing, China, pp237-267, 2013.

于洪，王滢，王国胤. 基于三支决策的重叠聚类方法. 刘盾，李天瑞，苗夺谦，王国胤，梁吉业编著. 三支决策与粒计算. 北京:科学出版社.2013 (2013年7月, 第11章).

6.         Hong Yu, Zhanguo Liu, Guoyin Wang. An Automatic Method to Determine The Clustering Number Decision Based on Rough Set. (Chapter 12), in Xiuyi Jia, Lin Shang, Xianzhong Zhou, Jiye Liang, Duoqian Miao, Guoyin Wang, Tianrui Li, Yanping Zhang (Eds.). Three-way Decision’Theory and Application. Nanjing:Nanjing University Press. Nanjing, China, 192-212, 2012.

于洪，刘占国，王国胤. 基于决策粗糙集的聚类数自动确定方法. 贾修一，商琳，周献中，梁吉业，苗夺谦，王国胤，李天瑞，张燕平编著. 三支决策理论与应用, 南京:南京大学出版社.2012(2012年10月, 第12章).

7.         Hong Yu, Guoyin Wang. Autonomous Clustering Method Based on Decision-theoretic Rough Set(chapter 5), in Huaxiong Li, Xianzhong Zhou, Tianrui Li,Guoyin Wang,Duoqian Miao,Yiyu Yao (Eds.), Three-way Decisions Theory and Research Advances. Beijing: Science Press. 92-114, 2011.

于洪，王国胤. 基于决策粗糙集的自动聚类方法. 李华雄, 周献中，李天瑞，王国胤，苗夺谦，姚一豫编著. 决策粗糙集理论及其研究进展. 北京:科学出版社. 2011(2011年11月,第5章).

1. Ying Xu;Weiru Liu;Guoyin Wang;Shihua Zhang;Hong Yu;Paul Miller;Tatsuya Akutsu (Eds.), 2023 IEEE International Conference on Medical Artificial Intelligence (MedAI)，18-19 Nov. 2023, Beijing, China, ISBN-13: 979-8-3503-5878-0 BMS Part # CFP23UO0-ART

2. Victor Chang, Yongxin Zhu, Hong Yu (Eds.), Second International Conference on Industrial IoT, Big Data, and Supply Chain, 15–17 October 2021, Online Only, Macao, China Proceedings of SPIE 0277-786X, V. 12128

3. Yiyu Yao, Qinghua Hu, Hong Yu, Jerzy W. Grzymala-Busse (Eds.), Rough sets, fuzzy sets, data mining, and granular computing. Proceedings of RSFDGrC 2015, LNAI 9437, Springer, Tianjin, China, 2015

4. Tianrui Li, Hung Son Nguyen , Guoyin Wang , Jerzy Grzymala-Busse , Ryszard Janicki , Aboul Ella Hassanien and Hong Yu(Eds.), Rough Sets and Knowledge Technology, Proceedings of RSKT2012, LNAI7414, Springer-Verlag, Chengdu, China, 2012

1.       Chenglin Zhang, Hong Yu, Guoyin Wang, et al. LiNGAM-SF: Causal Structural Learning Method With Linear Non-Gaussian Acyclic Models for Streaming Features. IEEE Transactions on Neural Networks and Learning Systems, 2025, 1-14. 

2.       Yan Xian, Hong Yu, Huaxiong Li, et al. Class Incremental Learning via Semantic Information Mapping and Background Information Calibrating. IEEE Transactions on Circuits and Systems for Video Technology, 2024, 34(12): 13373-13385. 

3.    Hong Yu, Zongqiang Wang, Yongfang Xie, et al. A Multi-Granularity Hierarchical Network for Long- and Short-Term Forecasting on Multivariate Time Series Data. Applied Soft Computing, 2024, 157: 111537.

4.       Hong Yu, Xuekang Fan, Guoyin Wang, et al. VSG3A2: A Genetic Algorithm-Based Virtual Sample Generation Approach Using Information Gain and Acceptance-Rejection Sampling. IEEE Transactions on Evolutionary Computation, 2024, 28(5): 1514-1528,.

5.       Hong Yu, Jiangnan Gong, Guoyin Wang, et al. A Hybrid Model for Billet Tapping Temperature Prediction and Optimization in Reheating Furnace. IEEE Transactions on Industrial Informatics, 2023, 19(8)：8703-8712. 

6.       Xu Xiang, Hong Yu, Ye Wang, et al. Stable local interpretable model-agnostic explanations based on a variational autoencoder. Applied Intelligence, 2023, 53: 28226–28240.

7.   Hong Yu, Qian Yang, Guoyin Wang, et al. A Novel Discriminative Dictionary Pair Learning Constrained by Ordinal Locality for Mixed Frequency Data Classification. IEEE Transactions on Knowledge and Data Engineering, 2022, 34(10): 4572-4585.

8.       Peng Wu, Hong Yu, Feng Hu, et al. A temporal‑attribute attention neural network for mixed frequency data forecasting. International Journal of Machine Learning and Cybernetics, 2022,13: 2519–2531.

9.       Hong Yu, Jia Tang, Guoyin Wang, et al. A Novel Multi-View Clustering Method for Unknown Mapping Relationships Between Cross-View Samples[C]//In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’21), 2021, 9: 2075-2083. 

10.    Hong Yu, Zhao Fu, Guoyin Wang, et al. A Multi-objective optimization algorithm based on dynamic user-preference information. Computing, 2022, 104(3): 627-656.

11.    ChaoFan He, Hong Yu, SongEn Gu, et al. A multi-granularity information-based method for learning high-dimensional Bayesian network structures. Cognitive Computation, 2022, 14(6): 1805-1817.

12.    Hong Yu, Xincheng Wang, Guoyin Wang, et al. An active three-way clustering method via low-rank matrices for multi-view data. Information Sciences, 2020, 507: 823-839.

13.    Hong Yu, Zhihua Chang, Guoyin Wang, et al. An efficient three-way clustering algorithm based on gravitational search. International Journal of Machine Learning and Cybernetics, 2020, 11: 1003-1016.

14.    Xiangpeng Li , Hong Yu , Yongfang Xie, et al. Attention-based novel neural network for mixed frequency data. CAAI Transactions on Intelligence Technology, 2021, 6(3): 301-311.

15.    Zhihan Peng, Hong Yu, Xiuyi Jia. Path-based reasoning with K-nearest neighbor and position embedding for knowledge graph completion. Journal of Intelligent Information Systems, 2021: 1-21. 

16.    Hong Yu, Xincheng Wang, Guoyin Wang, et al. An active three-way clustering method via low-rank matrices for multi-view data. Information Sciences, 2018, 507: 823-839.

17.    Hong Yu, Bing Zhou, Mingyao Deng, et al. Tag recommendation method in folksonomy based on user tagging status. Journal of Intelligent Information Systems, 2018, 50: 479-500.

18.    Hong Yu, Bing Zhou, Mingyao Deng, Feng Hu. Tag recommendation method in folksonomy based on user tagging status[J]. Journal of Intelligent Information Systems, 2018, 50(3):479-500.

19.    Hong Yu, Peng Jiao, Yiyu Yao, Guoyin Wang. Detecting and refining overlapping regions in complex networks with three-way decisions[J]. Information Sciences, 2016, 373:21-41.

20.    Hong Yu, Cong Zhang, Guoyin Wang. A tree-based incremental overlapping clustering method using the three-way decision theory[J]. Knowledge-Based Systems, 2016, 91:189-203.

21.    Hong Yu, Zhanguo Liu, Guoyin Wang. An automatic method to determine the number of clusters using decision-theoretic rough set[J]. International Journal of Approximate Reasoning, 2014, 55(1):101-115.

22.    Hong Yu, Qingfeng Zhou, Man Liu. A dynamic composite Web services selection method with QoS-aware based on AND/OR Graph[J]. International Journal of Computational Intelligence Systems, 2014, 7(4):660-675.

23.    Hong Yu, Shuangshuang Chu, Dachun Yang. Autonomous knowledge-oriented clustering using decision-theoretic rough set theory[J]. Fundamenta Informaticae, 2012, 115: 141–156.

24.    Hong Yu, Qingfeng Zhou, Man Liu. A Dynamic Composite Web Services Selection Method With QoS-Aware Based on AND/OR Graph[J]. International Journal of Computational Intelligence Systems, 2014, 7(4):660-675.

25.     Guoyin Wang, Xi’ao Ma, Hong Yu. Monotonic uncertainty measures for attribute reduction in probabilistic rough set model[J]. International Journal of Approximate Reasoning, 2015, 59(C):41-67.

26.     Xi’ao Ma, Guoyin Wang, Hong Yu, Tianrui Li. Decision region distribution preservation reduction in decision-theoretic rough set model[J]. Information Sciences, 2014, 278:614-640.

27.    于洪，何德牛, 王国胤, 李劼, 谢永芳. 大数据智能决策. 自动化学报, 2020, 46(5): 878-896.

Hong Yu, Deniu He, Guoyin Wang, Jie Li, Yongfang Xie. Big Data for Intelligent Decision      Making. Acta Automatica Sinica, 2020, 46(5): 878-896. 

28.    于洪, 王国胤, 姚一豫. 决策粗糙集理论研究现状与展望[J]. 计算机学报, 2015, 38(8): 1628-1639.

Hong Yu, Guoyin, Wang, Yiyu Yao. Current Research and Future Perspectives on Decision-Theoretic Rough Sets[J]. Chines Journal of Computers, 2015, 38(8): 1628-1639.

29.    于洪, 李俊华. 一种解决新项目冷启动问题的推荐算法[J]. 软件学报, 2015, 26(6): 1395−1408.

Hong Yu, Junhua Li. Algorithm to Solve the Cold-Start Problem in New Item Recommendations[J]. Journal of Software, 2015, 26(6): 1395−1408.

30.     马希骜, 王国胤, 于洪. 决策域分布保持的启发式属性约简方法[J]. 软件学报, 2014, 25(8):1761-1780.

Xi’ao Ma, Guoyin Wang, Hong Yu. Heuristic Method to Attribute Reduction for Decision Region Distribution Preservation[J]. Journal of Software, 2014, 25(8):1761-1780.

31.    于洪, 邓明瑶, 胡峰. 考虑用户标注状态的标签推荐方法[J]. 模式识别与人工智能, 2014, 27(8): 673-682.

Hong Yu, MingYao Deng, Feng Hu. Tag Recommendation Method Considering Users Tagging Status[J]. Pattern Recognition and Artificial Intelligence, 2014, 27(8): 673-682.

32.    于洪, 杨显. 微博中节点影响力度量与传播路径模式研究[J]. 通信学报, 2012, 33(Z1): 96-102.

Hong Yu, Xian Yang. Studying on the node’s influence and propagation path modes in microblogging[J]. Journal on Communications, 2012, 33(Z1): 96-102.

33.    于洪, 杨大春. 基于蚁群优化的多个属性约简的求解方法[J]. 模式识别与人工智能, 2011, 24(2): 176-184.

Hong Yu, Dachun Yang. Approach to Solving Attribute Reductions with Ant Colony Optimization[J]. Pattern Recognition and Artificial Intelligence, 2011, 24(2): 176-184.

34.    王国胤, 姚一豫, 于洪. 粗糙集理论与应用研究综述[J]. 计算机学报, 2009, 32(7): 1229-1246.

Guoyin Wang, Yiyu Yao, Hong Yu. A Survey on Rough Set Theory and Applications[J]. Chines Journal of Computers, 2009, 32(7): 1229-1246.

35.    王国胤, 于洪, 杨大春. 基于条件信息熵的决策表约简. 计算机学报, 2002, 25(7): 759-766.

Guoyin Wang, Hong Yu, Dachun Yang. Decision Table Reduction based on Conditional Information Entropy. Chinese Journal of Computers, 2002, 25(7): 759-766.

[1]    Hong Yu, Jia Tang, Guoyin Wang, Xinbo Gao. A Novel Multi-View Clustering Method for Unknown Mapping Relationships Between Cross-View Samples// In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’21), August 14-18, 2021, Virtual Event, Singapore. ACM, New York, NY, USA, 9 pages, 2075-2083. DOI: 10.1145/3447548.3467294

[2]    Jiangnan Gong, Hong Yu, Cheng Huang. PS-AENN based prediction model of billet temperature in industrial steelmaking process// Victor Chang, Muthu Ramachandran, Víctor Méndez Muñoz (eds): International Conference on Industrial IoT, Big Data and Supply Chain, SIST 218, Macao, SAR, China, September 15-17, 2020. Springer, Singapore, 2021:23-31. DOI: 10.1007/978-981-33-6141-6_3

[3]    Hong Yu, Mengnan Cui, Guoyin Wang, Xiaofang Chen. A Two-sided Matching Method Based on Multi-stage Dynamic Reference Points// Victor Chang, Muthu Ramachandran, Víctor Méndez Muño (eds): International Conference on Industrial IoT, Big Data and Supply Chain, SIST 218, Macao, SAR, China, September 15-17, 2020. Springer, Singapore, 2021: 303-311. DOI: 10.1007/978-981-33-6141-6_33

[4]    Zhihan Peng, Hong Yu. Knowledge Graph Representation Learning for Link Prediction with Three-Way Decisions// International Joint Conference on Rough Sets (IJCRS) 2021, Springer, Cham, 2021

[5]    Xinyang Liu, Hong Yu, Guoyin Wang, Lei Guo, et al. A multi-criteria ordered clustering algorithm based on PROMETHEE// Zhong Li, Chunrong Yuan, Jie Lu, Etienne E Kerre (eds): 14th International FLINS Conference (FLINS 2020), Volume 12, Cologne, Germany, August 18-21, 2020. World Scientific Proceedings Series on Computer Engineering and Information Science, 2020:43-51.

[6]    Mengnan Cui, Hong Yu, Hongliang Zhang, XiaofangChen. A Novel Matching Method for Supply and Demand Based on Three-Way Decisions// IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2019), Dalian, Liaoning, China, November 14-16, 2019. IEEE, 2019: 82-89.

[7]    Jing Xiong, Hong Yu. A Three-Way Clustering Algorithm via Decomposing Similarity Matrices for Multi-view Data with Noise// Mihálydeák T, Fan Min, Guoyin Wang, Mohua Banerjee, Ivo Düntsch, Zbigniew Suraj, Davide Ciucci (eds): Joint Conference On Rough Sets (IJCRS 2019), LNCS 11499, Debrecen, Hungary, June 17-21, 2019. Springer, Cham, 2019: 179-193. DOI: 10.1007/978-3-030-22815-6_15

[8]    Hong Yu. Three-Way Decisions and Three-Way Clustering// Hung Son Nguyen, Quang-Thuy Ha, Tianrui Li, Malgorzata Przybyla-Kasperek (eds): International Joint Conference on Rough Sets (IJCRS 2018), LNAI 11103, Quy Nhon, Vietnam, August 20-24, 2018. Springer, Cham, 2018:13-28. DOI: 10.1007/978-3-319-99368-3_2

[9]    Hong Yu, Guoyin Wang. An Efficient Gradual Three-Way Decision Cluster Ensemble Approach// Jesus Medina, Manuel Ojeda-Aciego, Jose Luis Verdegay, David A.Pelta, Inma P.Cabrera, Bernadette Bouchon-Meunier, Ronald R.Yager (eds): the 17^th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), CCIS 854, Cadiz, Spain, June 11-15, 2018. Springer, Cham, 2018:711-723.

[10] Hong Yu, Zuoyu Sun, Guoyin Wang, Jie Li, Yongfang Xie, Gang Guo. A Multi-granular Hierarchical Evaluation Model for Multiple Criteria Three Sorting// Hanghang Tong, Zhenhui(Jessie)Li, Feida Zhu, Jeffrey Yu (eds): 2018 IEEE International Conference on Data Mining Workshops (ICDMW 2018), Singapore, November 17-20, 2018.

[11] Ning Sun, Hong Yu. A Method to Determine the Number of Clusters Based on Multi-validity Index// Hung Son Nguyen, Quang-Thuy Ha, Tianrui Li, Malgorzata Przybyla-Kasperek (eds): International Joint Conference on Rough Sets (IJCRS 2018), LNAI 11103, QuyNhon, Vietnam, August 20-24, 2018. Springer, Cham, 2018: 427-439. DOI: 10.1007/978-3-319-99368-3_33

[12] Zhao Fu, Hong Yu, Hongliang Zhang, Xiaofang Chen. A Multi-objective Optimization Algorithm Based on Preference Three-way Decomposition// Weiru Liu, Fausto Giunchiglia, Bo Yang (eds): International conference on Knowledge Science, Engineering and Management (KSEM 2018), LNAI 11062, Changchun, China, August 17-19, 2018. Springer, Cham, 2018: 3-11.

[13] Jing Xiong, Hong Yu. An Adaptive Three-way Clustering Algorithm for Mixed-type Data// Michelangelo Ceci, Nathalie Japkowicz, Jiming Liu, George A. Papadopoulos, Zbigniew W. Ras (eds): International Symposium on Methodologies for Intelligent Systems (ISMIS 2018), LNAI 11177, Limassol, Cyprus, October 29-31, 2018. Springer, Cham, 2018: 379-388.  DOI: 10.1007/978-3-030-01851-1_36

[14] Yan Liu, Hong Yu. Dynamic Overlapping Community Discovery Based on Core Nodes// The 9th IEEE International Conference on Big Knowledge (ICBK 2018), Singapore, November 17-18, 2018. IEEE, 2018: 252-259.  DOI: 10.1109/ICBK.2018.00041

[15] Hong Yu, Zuoyu Sun, Guoyin Wang, Jie Li, Yongfang Xie, Gang Guo. A Multi-granular Hierarchical Evaluation Model for Multiple Criteria Three Sorting// Hanghang Tong, Zhenhui (Jessie) Li, Feida Zhu, Jeffrey Yu (eds): 2018 IEEE International Conference on Data Mining Workshops (ICDMW 2018), Singapore, November 17-20, 2018. IEEE, 2018: 487-494.

[16] Hong Yu, Jisen Yang, Xiaofang Chen, Zhong Zou, Guoyin Wang, Tao Sang. Soft Measuring Model of Superheat Degree in the Aluminum Electrolysis Production// Naoki Abe, Huan Liu, Calton Pu, Xiaohua Hu, Nesreen Ahmed, Mu Qiao, Yang Song, Donald Kossmann, Bing Liu, Kisung Lee, Jiliang Tang, Jingrui He, Jeffrey Saltz (eds): 2018 IEEE International Conference on Big Data (ICBD 2018), Seattle, WA, USA, December 10-13, 2018. IEEE, 2018: 2679-2684.

[17] Hong Yu, Zhihua Chang, Bing Zhou. A Novel Three-Way Clustering Algorithm for Mixed-Type Data// Xindong Wu, Tamer Ozsu, Jim Hendler, Ruqian Lu (eds): IEEE International Conference on Big Knowledge (ICBK 2017), Hefei, China, August 9-10, 2017. IEEE, 2017: 119-126.

[18] Hong Yu. A Framework of Three-Way Cluster Analysis// Lech Polkowski, Yiyu Yao, Piotr Artiemjew, Davide Ciucci, Dun Liu, Dominik Slezak, Beata Zielosko (eds): International Joint Conference on Rough Sets (IJCRS 2017), LNAI 10314, Olsztyn, Poland, July 3-7, 2017. Springer, Cham, 2017: 300-312.

[19] Hong Yu, Xincheng Wang, Guoyin Wang. A Semi-supervised Three-Way Clustering Framework for Multi-view Data//Lech Polkowski, Yiyu Yao, Piotr Artiemjew, Davide Ciucci, Dun Liu, Dominik Slezak, Beata Zielosko (eds): International Joint Conference on Rough Sets (IJCRS 2017), LNAI 10314, Olsztyn, Poland, July 3-7, 2017. Springer, Cham, 2017: 313-325.

[20] Hong Yu, Leijie Jin, Bing Zhou, Bin Xiao, Xianhua Zeng. An Event-based Approach to Overlapping Community Evolution by Three-way Decisions// 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA 2017), Beijing, China, March 10-12, 2017. IEEE, 2017: 772-778. DOI: 10.1117/12.460205

1.        专利号：ZL 2023 1 1848403.7

授权公告号：CN 117809854 B

申请人：重庆邮电大学

发明人：于洪;陈熙文;苏祖强;胡峰;代劲;王国胤

发明创造名称：一种基于医学因果知识嵌入的危险因素因果关系提取方法

专利申请日：2023年12月29日

授权公告日：2024年10月08日

2.        专利号：ZL 2024 1 0422193.3

授权公告号： CN 118366654 B

申请人：重庆邮电大学

发明人：于洪;孙世杰;苏祖强;王国胤

发明创造名称：一种基于跨模态知识蒸馏的肺癌风险预测方法

专利申请日：2024年04月09日

授权公告日：2024年12月20日

3.        专利号：ZL 2023 1 1485787.0

申请日：2023年11月08日

申请人：重庆邮电大学

发明人：于洪;刘志成;王烨;钟福金

发明创造名称：一种基于有限状态机的自动驾驶决策方法

授权公告日：2024年06月04日

4.        专利号：ZL 202311778674X

申请日：2023 年12 月22 日

申请人：重庆邮电大学

发明人：于洪,杨宗庆,胡峰,苏祖强,代劲,王国胤

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专利申请日： 2023年12月22日

授权公告日：2024年11月15日

5.      专利号：ZL 2022 1 1109829.6

申请日：2022年09月13日

申请人：重庆邮电大学

发明人：邓维斌，李洪兴，于洪，张艺腾，邓鹏

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授权公告日：2023年09月15日

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申请日：2023年08月04日

申请人：重庆邮电大学

发明人：王烨;廖靖波;于洪;黄昌豪;杨峻杰;卞政轩

发明创造名称：一种基于可控多空间特征解耦的开放域对话生成方法

授权公告日：2024年05月10日

7.     专利号：ZL 2020 1 1318973.1

申请日：2020年11月23日

申请人：重庆邮电大学

发明人：于洪，魏居明，胡峰，王国胤

发明创造名称：一种基于三支集成预测模型的工业加热炉钢温预测方法

授权公告日：2022年10月11日

8.      申请号：202211329319.X

申请人：重庆邮电大学

发明人：于洪，范学康，张晓霞

发明创造名称：一种基于遗传算法的多层陶瓷电容器中陶瓷粉质量检测方法

受理公告日：2022年10月27日

9.      申请号：202211238085.8

申请人：重庆邮电大学

发明人：王烨，廖靖波，于洪

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受理公告日：2022年10月1日

10.   专利号：ZL 2019 1 0554737.0

申请人：重庆邮电大学

发明人：崔梦楠, 于洪, 胡峰, 苏祖强, 王国胤

发明创造名称：基于三支决策的大型企业供需双方匹配方法

授权公告日：2022年3月22日

11.   专利号：ZL 2019 1 1292314.2

申请人：重庆邮电大学

发明人：张晓霞，罗乾豪，于洪

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授权公告日：2022年3月22日

12.   专利号：ZL 2019 1 0961446.3

申请人：重庆邮电大学

发明人：苏祖强，罗子澳，于洪，萧红，谢海琼，谭峰

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授权公告日：2021年7月6日

13.   专利号：ZL 2019 1 0429746.7

申请人：重庆邮电大学

发明人：于洪，杨倩，胡峰，王国胤，张晓霞

发明创造名称：面向混合采样工业大数据的基于多视图字典学习分类方法

授权公告日：2021年5月18日

14.   专利号：ZL 2017 1 0548072.3

申请人：重庆邮电大学

发明人：于洪，陈云，胡峰，王国胤，胡军

发明创造名称：基于Spark平台采用两次评价的加权选择集成三支聚类方法

授权公告日：2021年2月9日

授权公告号：CN 1074806940 B

15.   申请号：ZL 2018 1 1517670.5

申请人：重庆邮电大学

发明人：胡军，刘天娇，张清华，于洪，朱正禹

发明创造名称：面向身份联盟的多粒度联合身份认证方法

授权公告日：2020年12月4日

16.   专利号：ZL 2018 1 0500016.7

申请人：重庆邮电大学

发明人：胡峰，万志超，王国胤，于洪，张清华，刘柯，郭英杰，周雷，王驰龙

发明创造名称：一种基于Spark大数据平台的并行CRF方法

授权公告日：2020年11月17日

17.   专利号：ZL201910077715.X

申请人：重庆邮电大学

发明人：钟福金，闫硕，于洪

发明创造名称：一种基于多步加权的单样本部分遮挡人脸识别方法

授权公告日：2020年11月10日

18.   专利号：ZL 2016 1 1120326.3

申请人：重庆邮电大学

发明人：胡峰，瞿原，邓维斌，于洪，张清华

发明创造名称：基于Spark内存计算大数据平台的OPTICS点排序聚类方法

授权公告日：2020年8月4日

19.   专利号：ZL 2016 1 1259383.X

申请人：重庆邮电大学

发明人：胡峰，胡宗容，于洪，欧阳卫华，邓维斌，张清华

发明创造名称：一种基于MPI并行求信息系统属性约简的方法

授权公告日：2020年6月16日

20.     申请号：202010039863.5

申请人：重庆邮电大学

发明人：胡峰，赵志新，代劲，于洪

发明创造名称：一种基于多视图集成学习的煤矿瓦斯浓度预警方法

受理日期：2020年1月15日

21.     专利号：ZL 2016 1 1120338.6

申请人：重庆邮电大学

发明人：胡峰，张其龙，邓维斌，于洪，张清华

发明创造名称：基于Spark内存计算大数据平台的CLR多标签数据分类方法

授权公告日：2019年7月19日

22.     专利号：ZL 2016 1 1244051.4

申请人：重庆邮电大学

发明人：胡峰，王蕾，欧阳卫华，于洪，王进，雷大江，李智星，瞿原，赵蕊，张其龙

发明创造名称：基于Spark大数据平台的三支决策不平衡数据过采样方法

授权公告日：2019年7月19日

23.     专利号：ZL 2016 1 0100024.3

申请人：重庆邮电大学

发明人：胡峰，石瑾，于洪，张清华

发明创造名称：一种基于属性聚类的邻域粗糙集集成学习方法

授权公告日：2019年3月8日

24.     专利号：ZL 2014 1 0037999.7

申请人：重庆邮电大学

发明人：胡峰，向倞，于洪，娄华宾

发明创造名称：基于MapReduce的LBS兴趣点发现方法

授权公告日：2016年11月9日