IEEE Computational Intelligence Society

Fuzzy Systems Technical Committee

Task Force on “Complex Fuzzy Sets and Logic”

 

Task Force Chair:

  Scott Dick

  Department of Electrical & Computer Engineering, University of Alberta

  2nd Flr. ECERF Bldg.

  9107 – 116 Street, Edmonton, Alberta, Canada, T6G 2V4

  dick@ece.ualberta.ca

  http://www.ece.ualberta.ca/~dick  

 

  TF Chair’s Short CV: Prof. Scott Dick received his B.Sc. degree in 1997, his M.Sc. degree in 1999, and his Ph.D. in 2002, all from the University of South Florida. His Ph.D. dissertation received the USF Outstanding Dissertation Prize in 2003. From 2002 to 2008 he was an Assistant Professor of Electrical and Computer Engineering at the University of Alberta in Edmonton, AB. Since 2008, he has been an Associate Professor in the same department.

              Dr. Dick’s research interests are in Computational Intelligence, machine learning, data mining, and the application of these technologies to real-world problems (e.g. Smart Grid, livestock disease management, and anti-phishing technologies). A particular focus is the topic of “complex fuzzy logic,” an extension of type-1 fuzzy logic to complex-valued membership grades. His work has been funded by NSERC, the Alberta Science and Research Authority, Hewlett-Packard, PRECARN Inc., and Transport Canada. He is a member of the IEEE Computational Intelligence Society’s Fuzzy Systems Technical Committee. He is an Associate Editor for IEEE Transactions on Fuzzy Systems, as well as Evolving Systems. He is a member of the ACM, IEEE, and ASEE.

 

Task Force Vice-Chair:

  Dan E. Tamir

  Associate Professor of Computer Science

  Texas State University

  601 University Drive,

  San Marcos, Texas, 78666

  Office 512-245-7528

  Email: dt19@txstate.edu

  http://cs.txstate.edu/~dt19/

 

  TF Vice-Chair’s Short CV: Dan Tamir is an associate professor of Computer Science at the Texas State University, San Marcos, Texas (2005 - to date). He obtained the PhD-CS from Florida State University in 1989, and the MS/BS-EE from Ben-Gurion University, Israel.

              From 1996-2005, he managed applied research and design in DSP Core technology in Motorola-SPS/Freescale. From 1989-1996, he served as an assistant/associate professor in the CS Department at Florida Tech. Between 1983-1986, he worked in the applied research division, Tadiran, Israel.

              Dan is conducting research in fuzzy logic, power aware task scheduling, combinatorial optimization, computer vision, and data compression.  He has been a member of the Israeli delegation to the MPEG committee and a Summer Fellow at NASA KSC.

 

TF Members:

Francisco Chiclana

H.N. Teodorescu

Jun Ma

Mark Last

Sarah Greenfield

Vladik Kreinovich

 

Motivation:

Investigations into complex fuzzy sets (an extension of type-1 fuzzy sets wherein the membership function is complex-valued) have shown that these technologies are practical and offer improvements over existing approaches in certain fields. There is now a body of work showing that forecasting algorithms based on complex fuzzy sets can be more accurate, and more compact, than traditional neural network and neuro-fuzzy approaches. Several research groups around the world are investigating complex fuzzy sets, and the isomorphic complex fuzzy logic. This subfield would now clearly benefit from having a common point of contact with others interested in the topic, as well as increased exposure to the wider Computational Intelligence community. The creation of an FSTC Task Force on Complex Fuzzy Sets and Logic appears to be the best way to reach these goals. 

 

Goals:

The goal of this task force is to promote interest in, and the development of, complex fuzzy sets and logic.

 

Scope:

The scope of this task force includes both the theory of complex fuzzy sets and logic, and their application. The defining characteristic of complex fuzzy sets is that membership is vector valued; likewise, in the isomorphic complex fuzzy logic, truth values are vectors. This creates a number of theoretical challenges (e.g. defining the class of complex fuzzy intersection operators). Likewise, operationalizing complex fuzzy sets and logic for a practical application carries its own challenges (e.g. linguistic interpretation of a complex fuzzy set). All of these topics are within the scope of this task force.   

 

Planned Activities:

-        Propose a special session on “Complex Fuzzy Sets and Logic” for FUZZ-IEEE 2015

-        Prepare and submit a review article on “Complex Fuzzy Sets and Logic” for IEEE Trans. Fuzzy Systems, 2014.

-        Establish a Web presence; including a website and social media.