Soft Computing in Case Based Reasoning

  • Sankar K. Pal
  • Tharam S. Dillon
  • Daniel S. Yeung

Table of contents

  1. Front Matter
    Pages i-xix
  2. A Tutorial on Case Based Reasoning

    1. Julie Main, Tharam S. Dillon, Simon C. K. Shiu
      Pages 1-28
  3. Fuzzy Sets

    1. Hans-Dieter Burkhard, Michael M. Richter
      Pages 29-45
    2. Eyke Höllermeier, Didier Dubois, Henri Prade
      Pages 47-72
  4. Artificial Neural Networks

  5. Genetic Algorithms

    1. Amilcar Cardoso, Ernesto Costa, Penousal Machado, Francisco C. Pereira, Paulo Gomes
      Pages 147-177
    2. Benjamin W. Wah, Arthur Ieumwananonthachai
      Pages 179-211
  6. Neuro-Fuzzy Computing

  7. Applications

  8. Back Matter
    Pages 367-372

About this book


Soft Computing in Case Based Reasoning demonstrates how various soft computing tools can be applied to design and develop methodologies and systems with case based reasoning for real-life decision-making or recognition problems.
Comprising contributions from experts from all over the world, it:
- Provides an introduction to CBR and soft computing, and the relevance of their integration
- Evaluates the strengths and weaknesses of CBR in its current form
- Presents recent developments and significant applications in domains such as data-mining, medical diagnosis, knowledge-based expert systems, banking, and forensic investigation
- Addresses new information on developing intelligent systems
This book will be of particular interest to graduate students and researchers in computer science, electrical engineering and information technology but it will also be of interest to researchers and practitioners in the fields of systems design, pattern recognition and data mining.


artificial intelligence artificial neural network case-based reasoning data mining expert system fuzzy logic fuzzy sets genetic algorithms genetics heuristics intelligence learning memory neural networks pattern recognition

Editors and affiliations

  • Sankar K. Pal
    • 1
  • Tharam S. Dillon
    • 2
  • Daniel S. Yeung
    • 3
  1. 1.Machine Intelligence UnitIndian Statistical InstituteCalcuttaIndia
  2. 2.Department of Computer Science and Computer EngineeringLa Trobe UniversityBundoora, MelbourneAustralia
  3. 3.Department of ComputingThe Hong Kong Polytechnic UniversityHunghom, KowloonHong Kong

Bibliographic information

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