Soft Computing Methods

  • N. C. Chauhan
  • M. V. Kartikeyan
  • A. Mittal
Part of the Studies in Computational Intelligence book series (SCI, volume 392)


In this chapter, a brief introduction to different soft computing methods, namely, genetic algorithms, particle swarm optimization, bacterial foraging optimization, neural networks and support vector machine has been presented. The overall presentation is separated into sections like evolutionary algorithms, swarm intelligence based algorithms, and methods of learning. Among these methods, genetic algorithms and neural networks have been well explored by microwave researchers, however rest of the techniques are still not much investigated. The rest of the book chapters focuses much on the investigation of these relatively new techniques and their modifications to microwave and millimeter-wave design problems.


Genetic Algorithm Support Vector Machine Support Vector Regression Swarm Intelligence Neural Network Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Information TechnologyA.D. Patel Institute of TechnologyAnandIndia
  2. 2.Department of Electronics andIndian Institute of TechnologyRoorkeeIndia
  3. 3.Research & ConsultancyCollege of EngineeringRoorkeeIndia

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