Dongrui Wu Defense

Abstract:This research is focused on multi-criteria decision-making (MCDM) under uncertainties, especially linguistic uncertainties. This problem is important because many times linguistic information, in addition to numerical information, is an essential input of decision-making. Linguistic information usually conveys more uncertainty, and it is necessary to incorporate and propagate this uncertainty during the decision-making process because uncertainty means risk.MCDM problems can be classified into two categories: 1) multi-attribute decision-making (MADM), which selects the best alternative(s) from a group of candidates using multiple criteria, and 2) multi-objective decision-making (MODM), which optimizes conflicting objective functions under constraints. Perceptual computer, an architecture for computing with words, is implemented in this dissertation for both categories. For MADM, we consider the most general case that the weights for and the inputs to the criteria are a mixture of numbers, intervals, type-1 fuzzy sets and/or words modeled by interval type-2 fuzzy sets. Novel weighted averages are proposed to aggregate this diverse and uncertain information so that the overall performance of each alternative can be computed and ranked. For MODM, we consider how to represent the dynamics of a process (objective function) by IF-THEN rules and then how to perform reasoning based on these rules, i.e., to compute the objective function for new linguistic inputs. Two approaches for extracting the IF-THEN rules are proposed: 1) linguistic summarization to extract rules from data, and 2) a knowledge mining approach to extract rules through survey. Applications are shown for all approaches proposed in this dissertation.Bio:Dongrui Wu received a B.E in Automatic Control from the University of Science and Technology of China, Hefei, Anhui, P.R. China, in 2003, an M.Eng in Electrical Engineering from the National University of Singapore, Singapore, in 2005, and an MS in Electrical Engineering from the University of Southern California, Los Angeles, CA, in 2008. Currently he is pursuing his Ph.D. in Electrical Engineering at USC. His research interests include computational intelligence, information fusion, machine learning, decision-support systems, signal processing, control theories, and their applications to smart oilfield technologies. Dongrui Wu has more than 20 publications, including a book (co-authored with J. M. Mendel) "Perceptual Computing: Aiding People in Making Subjective Judgments'' by the Wiley-IEEE Press, and a Best Student Paper Award from the 2005 IEEE International Conference on Fuzzy Systems.

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 403

Audiences: Everyone Is Invited

Contact: Gloria Halfacre