学术报告

报告题目： Deterministic and Stochastic Fuzzy Discrete

 Event Systems with Supervised Learning

报 告 人：美国韦恩州立大学  Hao Ying （应浩）教授

报告时间：2025年5月27日上午8:30-10:30

报告地点：九章楼311

摘    要：

In this presentation, we show our recent work on how a FDES can learn the event transition matrix of its fuzzy automaton, which is the core of the FDES that is difficult to build manually, when neither pre-event nor post-event state is known. The only information assumes to be available is values of the variables that are only known to be vaguely related to the pre- and post-event states. We link the variables to the states through Gaussian fuzzy sets owing to the conceptual relationship between a fuzzy set and a fuzzy state. Stochastic-gradient-descent-based algorithms are derived for the model to iteratively learn online the transition matrix and all the parameters of the fuzzy sets simultaneously. This leads to the first FDES model that is capable of learning solely based on sensor data without relying on any subjective input from humans, removing a significant bottleneck for real-world applications.

报告人简介：

Dr. Hao Ying (应浩 in Chinese) is a Professor in the Department of Electrical and Computer Engineering at Wayne State University, Michigan, USA. He published a single-author research monograph/advanced textbook, “Fuzzy Control and Modeling: Analytical Foundations and Applications” (IEEE Press, 2000, 342 pages; foreword by Professor Lotfi A. Zadeh), showcasing his extensive original research findings. Additionally, he coauthored the book “Introduction to Type-2 Fuzzy Logic Control: Theory and Applications” (IEEE Press and John Wiley & Sons, Inc., 2014). Dr. Ying's scholarly output includes over 130 peer-reviewed journal papers and more than 160 peer-reviewed conference papers. He holds a Google Scholar h-index 52, with over 12,000 total citations, positioning him within the top 25% of the 100,000 most-cited authors across all 22 scientific fields (176 subfields)*. He received the 2023 IEEE CIS Fuzzy Systems Pioneer Award, the highest honor from the IEEE Computational Intelligence Society, with the citation “For fundamental contributions to model-free fuzzy control theory and its biomedical applications.”