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  • © 2002

Advances in Computational Intelligence and Learning

Methods and Applications

Part of the book series: International Series in Intelligent Technologies (ISIT, volume 18)

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Table of contents (35 chapters)

  1. Front Matter

    Pages i-xvi
  2. Methodologies

    1. Front Matter

      Pages 1-1
    2. Accuracy and Transparency of Fuzzy Systems

      • Robert Babuška
      Pages 3-16
    3. Should Tendency Assessment Precede Rule Extraction by Clustering? (No!)

      • James C. Bezdek, Nikhil R. Pal, Thomas A. Runkler, Kuhu Pal
      Pages 17-41
    4. An Evaluation of Confidence Bound Estimation Methods for Neural Networks

      • Luren Yang, Tom Kavli, Mats Carlin, Sigmund Clausen, Paul F. M. De Groot
      Pages 71-84
    5. Predictive Control with Restricted Genetic Optimisation

      • Santiago Garrido, Luis Moreno, Miguel Angel Salichs
      Pages 107-116
    6. Neuro-Fuzzy Systems for Rule-Based Modelling of Dynamic Processes

      • Marian B. Gorzalczany, Adam Gluszek
      Pages 135-146
    7. Hybrid Intelligent Architectures using a Neurofuzzy Approach

      • Liam P. Maguire, T. Martin McGinnity, Brendan P. Glackin
      Pages 147-158
    8. Advances in Machine Learning

      • Maarten W. van Someren
      Pages 183-192
    9. Symbolic and Neural Learning of Named-Entity Recognition and Classification Systems in Two Languages

      • G. Petasis, S. Petridis, G. Paliouras, V. Karkaletsis, S. J. Perantonis, C. D. Spyropoulos
      Pages 193-210
    10. Fuzzy Model-Based Reinforcement Learning

      • Martin Appl, Wilfried Brauer
      Pages 211-223
    11. A Cellular Space for Feature Extraction and Classification

      • Christian Kuhn, Jürgen Wernstedt
      Pages 225-243
  3. Applications

    1. Front Matter

      Pages 245-245
    2. A Fuzzy Approach to Taming the Bullwhip Effect

      • Christer Carlsson, Robert Fullér
      Pages 247-262

About this book

Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.

The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.

Bibliographic Information

Buy it now

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access