Soft Computing Methods, Modeling and Simulation in Electrical Engineering

Soft computing methods have become fairly common in various fields over the last few decades. But it is relatively recent, and still to a very limited extend, that their potential in association with electrical engineering has come to be realized and explored. Numerous advances have been made in modeling, simulation and developing intelligent systems, some inspired by soft computing methods. Researchers from many scientific disciplines are designing systems with artificial intelligence to solve a variety of problems in pattern recognition, prediction, optimization and control. Conventional approaches have been proposed for solving these problems. Although successful applications can be found in certain well-constrained environments, none is flexible enough to perform well outside its domain. Soft computing methods provide exciting alternatives, and many applications could benefit from using them.

Topics:

  1. Applications of fuzzy systems
  2. Artificial neural networks
  3. Genetic algorithms
  4. Chaos theory and bio-inspired computation
  5. Modeling and simulation of technical problems in the area of electrical engineering
  6. Classification and clustering, i.e. in electrical machines, electrical drives, power semiconductor systems, power engineering, electrical measurement, signal processing, robotics, control theory and systems etc.

Co-Chairs
  • Ajith Abraham, Machine Intelligence Research Labs (Europe)
  • Vaclav Snasel, VSB-Technical University of Ostrava (Czech Republic)
  • Pavel Brandstetter, VSB-Technical University of Ostrava (Czech Republic)

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