TUTORIAL

System Identification Using Evolutionary Algorithms
     
within the
9th WSEAS International Conference on
APPLIED MATHEMATICS (MATH '06)
Istanbul, Turkey, May 27-29, 2006
http://www.worldses.org/conferences/2006/istanbul/math/index.html
 

Content:

In the last decade, Evolutionary Algorithms (EA) has been among the very important development for solving complex optimization problems. EAs made a great success on solving difficult optimization problems in both computer science and engineering fields. It becomes the engine of a field known today as Evolutionary Computation (EC). There are wide classes of real word problems for which no adequate solutions based available algorithms exist. There are two classes of algorithms often use to handle such problems, deterministic and stochastic algorithm. EAs are a class of stochastic search algorithms which include Genetic Algorithms (GAs) (Holland 1975), Evolutionary Strategies (ESs) (Rechenberg 1973) and Genetic Programming (GP) (Koza 1991). These algorithms are crude simplifications of biological reality; they can yield very robust, direct computer algorithms.

The objective of this tutorial is to describe the structure of evolutionary algorithms, the representation operators, selection mechanisms, and how they can be used to solve system identification problems. We plan to provide many examples about possible applications of EAs in system identification, control, forecasting, car-engine design and industrial processes.

Organizer:

Asc. Professor Alaa Sheta, Department of Information Technology, Prince Abullah Bin Ghazi Faculty of Science and Information Technology, Al-Balqa Applied University, P. O Box 7002, Salt 19117, JORDAN

Detailed Contents:

  1. System Identification Concept

  2. Review of Linear and Nonlinear Systems

  3. Modeling Nonlinear Systems Difficulties and Challenges

  4. Review of Traditional Modeling Techniques

  5. Overview of Genetic Algorithms (GAs)

  6. Overview of Genetic Programming (GP)

  7. Software Tools for GAs and GP.

  8. Case Studies

Textbooks:

  • T. Baeck, D. B. Fogel, and Z. Michalewicz (eds.). Handbook on Evolutionary Computation. IOP Press, 1997.
  • Z Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs (3rd edition). Springer-Verlag, Berlin, 1996.
  • W Banzhaf, P Nordin, R E Keller & Frank D Francone. Genetic Programming: An Introduction. Morgan Kaufmann, 1999.
  • X. Yao (ed). Evolutionary Computation: Theory and Applications. World Scientific Publ. Co., Singapore, 1999. (ISBN 3-540-65907-2)


 HOW TO SUBMIT:

 

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IMPORTANT DATES and MORE INFORMATION FOR THE SESSION:


 http://www.worldses.org/conferences/2006/istanbul/math/index.html

 

Brief Biography of the Organizer:

Dr. Alaa Sheta is an Associate Professor with the Information Technology Department, Al- Balqa Applied University. He received his Ph.D. from the School of Information Technology, George Mason University in 1997. Dr. Sheta’s research interest includes modeling and simulation of nonlinear systems, evolutionary algorithms (EA), fuzzy logic, neural networks, machine learning, and adaptive systems. He is also interested in experience-based learning in which systems must improve their performance while actually performing the desired tasks in uncertain and dynamically changing environments. He developed a number of methods for system identification and control of nonlinear dynamical systems in noisy environments. Dr. Sheta has published about 25 papers and a book chapter, most of them is in the area of evolutionary algorithms applications for engineering and computer science. He has been a plenary speaker at number of events on evolutionary algorithms. He is an active member of the EA research community and has been involved in organizing number of special sessions within international conferences and a co-chair for a number of workshops in this area. Dr. Sheta received number of grants from the US-Egypt Scientific Board in the area of fault detection and diagnosis using genetic programming. He is currently involved in research project sponsored by the National Science Foundation (NSF), USA with a collaborator from the Tennessee Technological University, Tennessee, USA. Dr. Sheta was a co-organizer of a special session,” Evolutionary Algorithms Aided Control Systems Design (EAACSD)” which was held in conjunction with the CEC2000.