Soft Computing in Industrial Applications

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  • Editors
  • Ashraf Saad
  • Keshav Dahal
  • Muhammad Sarfraz
  • Rajkumar Roy

Part of the Advances in Soft Computing book series (AINSC, volume 39)

Table of contents

  1. Front Matter
  2. Invited Keynote

    1. Pieter J. Mosterman, Elisabeth M. O’Brien
      Pages 1-16
  3. Part I: Soft Computing in Computer Graphics, Imaging and Vision

    1. Front Matter
      Pages 17-17
    2. Muhammad Sarfraz, Ali Taleb Ali Al-Awami
      Pages 19-29
    3. Juan Wachs, Helman Stern, Yael Edan, Michael Gillam, Craig Feied, Mark Smith et al.
      Pages 30-39
    4. I. De Falco, A. Della Cioppa, D. Maisto, E. Tarantino
      Pages 40-49
    5. Balazs Feil, Janos Abonyi
      Pages 50-59
  4. Part II: Control Systems

    1. Front Matter
      Pages 61-61
    2. Xiaojun Ban, X. Z. Gao, Xianlin Huang, Hang Yin
      Pages 63-71
    3. Leandro dos Santos Coelho, Fabio A. Guerra
      Pages 82-91
  5. Part III: Pattern Recognition

    1. Front Matter
      Pages 103-103
    2. Patricia Melin, Alejandra Mancilla, Miguel Lopez, Daniel Solano, Miguel Soto, Oscar Castillo
      Pages 105-114
    3. Boleslaw K. Szymanski, Lijuan Zhu, Long Han, Mark Embrechts, Alexander Ross, Karsten Sternickel
      Pages 144-155
  6. Part IV: Classification

    1. Front Matter
      Pages 157-157

About these proceedings


Soft Computing admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments. "Soft Computing in Industrial Applications" contains a collection of papers that were presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.


Wrapper classification cognition data mining evolution genetic algorithm genetic programming kernel machine learning modeling neural network optimization pattern recognition programming uncertainty

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-70704-2
  • Online ISBN 978-3-540-70706-6
  • Series Print ISSN 1615-3871
  • Series Online ISSN 1860-0794
  • About this book