基本情况

于福生，北京师范大学数学科学学院教授，博士生导师，北京师范大学“复杂系统智能控制”重点实验室主任。

 

主要经历

分别于1986年、1989年、1998年在北京师范大学数学系获得理学学士、硕士、博士学位。2003-2004在加拿大作访问学者，主要从事时序数据集合上的粒化以及知识发现与数据挖掘的研究。

曾担任汪培庄教授主持的国家自然科学基金重大项目“模糊信息处理与机器智能”领导小组秘书，并作为核心成员参加其中的一项子课题；作为项目组主要成员，先后参加了多项国家自然科学基金项目，博士点基金项目；作为主持人，先后承担了多项国家自然科学基金项目、省部级研究项目、校级研究项目和其他应用项目。

曾担任多个国际会议的程序委员会委员，区域组织委员会主席；担任过国际刊物评论员和Guest Editor. 已在国内外学术期刊和会议上发表科研论文90多篇，著译书2部。

1989年毕业留校在数学系工作至今，曾担任数学系副系主任，分管教学工作。现在是北京师范大学重点实验室——复杂系统智能控制实验室主任，国家教育部“数学与复杂系统”重点实验室成员。

 

获奖经历

曾研制了“故障诊断专家系统开发工具”（国家自然科学基金研究成果），开发了“高考试题难度预测专家系统”，并通过了正式的专家鉴定；该方面的论文曾获得电工学会、中国考试研讨会优秀论文奖，并作大会报告。

 

研究方向

模糊信息粒化、粒计算、数据挖掘


科研项目 

  1. 国家自然科学基金项目，基于粒化与知识指导的大规模异构值属性图序列的建模与挖掘及应用，2024-2027，主持。
  2. 国家自然科学基金项目，基于模糊信息粒化和知识指导的大规模区间值属性图序列的数据挖掘，2020-2023，主持。
  3. 国家自然科学基金项目，基于知识指导和模糊信息粒化的时序大数据分析和挖掘，2016-2019，主持。
  4. 北京市自然科学基金项目，基于知识指导和优化模糊信息粒化的大规模时序数据聚类和预测, 2011-2013，主持。
 

论文发表

  1. Yanan J, Fusheng Y, Yuqing T, Chenxi O, Fangyi L, et al. Trend-pattern Unlimited Fuzzy Information Granule-Based LSTM Model for Long-Term Time-Series Forecasting[J], International Journal of Approximate Reasoning, 2025
  2. Fangyi L, Fusheng Y, Liang S, Hexi L, Xiaonan Y, Qiang S, et al. EEG-Based Emotion Recognition with Combined Fuzzy Inference Via Integrating Weighted Fuzzy Rule Inference and Interpolation[J], MATHEMATICS, 2025, 13(1)
  3. Jiaqi C, Fusheng Y, Chenxi O, Huilin Y, Qian H, Lian Y, et al. An Interval-Valued Matrix Factorization Based Trust-Aware Collaborative Filtering Algorithm for Recommendation Systems[J], INFORMATION SCIENCES, 2025, 686
  4. Huiguo T, Shihu L, Yi T, Fusheng Y, et al. Multi-view Clustering Based on Pairwise Co-Regularization and Robust Dual Graph Non-Negative Matrix Factorization[J], Neurocomputing, 2025, 611(C)
  5. Yuqing T, Fusheng Y, Wenyi Z, Chenxi O, Yanan J, Yuming L, et al. Causalities-multiplicity Oriented Joint Interval-Trend Fuzzy Information Granulation for Interval-Valued Time Series Multi-Step Forecasting[J], INFORMATION SCIENCES, 2025, 694
  6. Chenxi Ouyang, Fusheng Yu, Fei Yang. Equipping High-order Fuzzy Cognitive Map with Interpretable Weights for Multivariate Time Series Forecasting[J], APPLIED SOFT COMPUTING, 2025, 170
  7. Yuqing T, Fusheng Y, Witold P, Fang L, Chenxi O, et al. Oriented to a Multi-Learning Mode: Establishing Trend-Fuzzy-granule-based LSTM Neural Networks for Time Series Forecasting[J], APPLIED SOFT COMPUTING, 2024, 166
  8. Yuqing Tang, Fusheng Yu, Witold Pedrycz. Synergizing Two Types of Fuzzy Information Granules for Accurate and Interpretable Multi-Step Forecasting of Time Series[J], IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2024, 32(10): 5910-5923.
  9. Yinhua G, Jiayin W, Fusheng Y, Cunqin S, et al. Variable Universe Fuzzy Control Based on Adaptive Error Integral for Uncertain Nonlinear Systems with Time-Delay[J], Intelligent Systems and Computing Lecture Notes on Data Engineering and Communications Technologies, 2024: 3-27.
  10. Huilin Y, Fusheng Y, Witold P, Zonglin Y, Jiaqi C, Jiayin W, et al. An Auto-Weighted Enhanced Horizontal Collaborative Fuzzy Clustering Algorithm with Knowledge Adaption Mechanism[J], INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2024, 169
  11. Chenxi O, Fei Y, Fusheng Y, Witold P, Wladyslaw H, Jiaqi C, Qian H, Zonglin Y, et al. Constructing Spatial Relationship and Temporal Relationship Oriented Composite Fuzzy Cognitive Maps for Multivariate Time Series Forecasting[J], IEEE Transactions on Fuzzy Systems, 2024, 32(8): 4338-4351.
  12. Fei Y, Fusheng Y, Chenxi O, Yuqing T, et al. Design Trend Fuzzy Granulation-Based Three-Layer Fuzzy Cognitive Map for Long-Term Forecasting of Multivariate Time Series[J], IEEE Trans Fuzzy Syst, 2024, 32(12): 7037-7049.
  13. Haoran W, Fusheng Y, Yuqing T, Chenxu W, et al. Linear Fuzzy Information Granule and Soft Subspace Based Multivariate Time Series Clustering[J], 2024 20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), 2024: 1-7.
  14. Huilin Y, Fusheng Y, Zhifang B, Yingying Z, Jiayin W, et al. With A Knowledge Adaption Mechanism: A Novel Horizontal Collaborative Fuzzy Clustering Method.[J], ICNC-FSKD, 2023: 1-8.
  15. Xiyang Y, Fusheng Y, Witold P, Zhiwei L, et al. Clustering Time Series under Trend-Oriented Fuzzy Information Granulation[J], APPLIED SOFT COMPUTING, 2023, 141
  16. Zhifang B, Huilin Y, Yingying Z, Yuming L, Fusheng Y, Lian Y, et al. Knowledge-Guidance Based Directed Graph Clustering.[J], ICNC-FSKD, 2023: 1-7.
  17. Yihan W, Fusheng Y, Wladyslaw H, Witold P, Agnieszka J, Xiao W, et al. Training Novel Adaptive Fuzzy Cognitive Map by Knowledge-Guidance Learning Mechanism for Large-Scale Time-Series Forecasting[J], IEEE Transactions on Cybernetics, 2023, 53(7): 4665-4676.
  18. Xueyan X, Fusheng Y, Witold P, Xubo D, et al. Multi-source Fuzzy Comprehensive Evaluation.[J], Applied Soft Computing, 2023, 135: 110042-110042.
  19. Pawel W, Kacper W, Wladyslaw H, Chenxi O, Fusheng Y, et al. Time Series Classification Based on Fuzzy Cognitive Maps and Multi-Class Decomposition with Ensembling[J], 2023 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, FUZZ, 2023
  20. Yingying Z, Fusheng Y, Huilin Y, Zhifang B, Shihu L, et al. Knowledge-Guidance Based Multi-Relational Graph Spectral Clustering Using a Novel Structural Similarity Measure[J], International Conference on Intelligent Systems and Knowledge Engineering, 2023: 195-203.