报告人简介：
Dr. HaoYing is a professor at the Department of Electrical and Computer Engineering,Wayne State University, USA. He has published one single-author book entitled FuzzyControl and Modeling: Analytical Foundations and Applications (IEEE Press,2000; foreword by Professor Lotfi A. Zadeh). He has recently coauthored anotherbook titled Introduction to Type-2 Fuzzy Logic Control: Theory and Applications(IEEE Press and John Wiley & Sons, Inc., 2014). In addition, he haspublished over 100 peer-reviewed journal papers and 150 conference papers. Hiswork has been widely cited - his Google Scholar h-index is 41. He is serving asan Associate Editor or a Member of Editorial Board for eight internationaljournals, including the IEEE Transactions on Fuzzy Systems. He serves as amember of the Fuzzy Systems Technical Committee of the IEEE ComputationalIntelligence Society and was elected to serve as a board member of the NorthAmerican Fuzzy Information Processing Society for two terms. He served asProgram Chair for three international conferences and also served as a ProgramCommittee Member for over 70 international conferences. He is an IEEE Fellow.
报告摘要：To effectivelyrepresent deterministic uncertainties and vagueness as well as human subjectiveobservation and judgment encountered in many real-world problems especiallythose in medicine, we recently originated a theory of fuzzy discrete eventsystems (DES). We introduced fuzzy states and fuzzy event transition andgeneralized conventional crisp DES to fuzzy DES. The largely graph-based frameworkof the crisp DES was unsuitable for the expansion and we thus reformulated itusing state vectors and event transition matrices which could be extended to fuzzyvectors and matrices by allowing their elements to take values in [0, 1]. We alsoextended optimal control of DES to fuzzy DES. The new fuzzy DES theory isconsistent with the existing theory, both at conceptual and computation levels,in that the former contains the latter as a special case when the membershipgrades are either 0 or 1. We further developed the FDES theory so that itpossessed self-learning capability.
We have applied the fuzzy DES theory todevelop an innovative software system for medical treatment, specifically forthe first round of highly active antiretroviral therapy of HIV/AIDS patients.The objective is to build such a system whose treatment regimen choice for anygiven patient will match expert AIDS physician’s selection to produce the (anticipated)optimal treatment outcome. Preliminary retrospective evaluation of ourprototype system using patients treated in our institution’s AIDS Clinical Center demonstratesencouraging results when the system operates in either self-learning mode ornon-learning mode. Our approach has the capabilities of generalizing, learning,representing knowledge even in the face of weak consensus of domain experts,and being readily upgradeable to new medical knowledge. These are practically importantfeatures to medical applications in general, and HIV/AIDS treatment inparticular, as national HIV/AIDS treatment guidelines are modified severaltimes per year.
Thisresearch was supported in part by the National Institutes of Health undergrantR21 EB001529-01A1, and by Wayne State University under aResearch Enhancement Program grant.
主持人：丁永生教授
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