T4: Bacterial Algorithms in Building Fuzzy Models from I/O Data

Laszlo T. Koczy
Szechenyi Istvan University (SZE, Gyor) and
Budapest University of Technology and Economics (BME) Hungary


A. Classic rule based fuzzy models
- 1. Rule interpolation
---- The problem of combinatorial explosion with fuzzy models
---- Sparse fuzzy rule bases, lack of complete and consistent information
---- Analogical reasoning and gradual rules
---- The Fundamental Equation of Fuzzy Rule Interpolation
---- Examples
- 2. Hierarchical fuzzy rule bases
---- Sugeno¡¯s fuzzy helicopter control
---- Local dimensionality reduction
---- A general model of hierarchical fuzzy control / reasoning models
- 3. Interpolation of hierarchical rule bases
---- Local cylindrical behavior of I/O data
---- Interpolation of sub-rule bases
---- A general algorithm for interpolation in hierarchical and sparse fuzzy rule models

B. Fuzzy Rule Model Identification
- 4.  Model identification by clustering (flat systems)
---- Fuzzy c-means clustering and fuzzy rule generation from I/O data
---- Examples, problems
- 5. MI by clustering (hierarchical systems)
---- A complex MI procedure for hierarchical fuzzy rule bases
---- A real life example: petroleum mining
- 6.  MI by bacterial memetic algorithm
---- Bacterial evolutionary algorithms a global search tool
---- Levenberg-Marquardt algorithm a local optimization tool
---- Various BMA approaches (combinations of the two), methods and simple examples
---- Three benchmark problems solved by BMA fuzzy MI




Laszlo T. Koczy received the M.Sc., M.Phil. and Ph.D. degrees from the Technical University of Budapest (BME) in 1975, 1976 and 1977, respectively; and the (postdoctoral) D.Sc. degree from the Hungarian Academy of Science, all in Electrical/Control Engineering. He spent most of his career at BME until 2001 and from 2002 at SZE. However, he has been a visiting professor at various universities abroad, namely in Australia (ANU, Murdoch and UNSW), Japan (TIT), Korea (POSTECH), Austria (J. Kepler U.), Italy (U. of Trento) and New Zealand Brazil, China, Finland and Poland for summer schools.

He was one of the LIFE Endowed Fuzzy Theory Chair Professors at Tokyo Institute of Technology and advisor to the Laboratory for International Fuzzy Engineering Research in Yokohama. His focus of research interest is fuzzy systems and Computational Intelligence topics (evolutionary algorithms, neural networks), as well as applications. He has published over 390 refereed papers and several text books on the subject. He introduced the concept of rule interpolation in sparse fuzzy models, and applied it successfully to the control of an automatic guided vehicle; further hierarchical interpolative fuzzy systems and fuzzy Hough transform. This latter provided the key technology in the winning vehicle in the 2007 Hungarian Mars Rover Competition. His research interests include applications of CI for telecommunication, transportation, vehicles and mobile robots, control, information retrieval, etc.

Among others he had been an Associate Editor of IEEE TFS and he is an Associate Editor of Fuzzy Sets and Systems, Int. J. of Fuzzy Systems, J. of Advanced Computational Intelligence, Mathware and Soft Computing, etc. He was the General Chair of FUZZ-IEEE 2004 in Budapest, and a number of other conferences, co-chair, PC member, etc. at many other scientific events. He served in the International Fuzzy Systems Association as President, and is now Administrative Committee member of the IEEE Computational Intelligence Society.