Soft Computing in Case Based Reasoning
Published on 6. December 2012
XIX, 372 pages
978-1-4471-0687-6 (ISBN)
Description
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.
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.
More details
Other editions
Additional editions
Sankar Kumar Pal | Tharam S. Dillon | Daniel S. Yeung
Soft Computing in Case Based Reasoning
Book
10/2000
Springer
€85.55
Article exhausted; check different version
Content
1. A Tutorial on Case Based Reasoning.- Fuzzy Sets.- 2. On the Notion of Similarity in Case Based Reasoning and Fuzzy Theory.- 3. Formalizing Case Based Inference Using Fuzzy Rules.- Artificial Neural Networks.- 4. Hybrid Approaches for Integrating Neural Networks and Case Based Reasoning: From Loosely Coupled to Tightly Coupled Models.- 5. Towards Integration of Memory Based Learning and Neural Networks.- Genetic Algorithms.- 6. A Genetic Algorithm and Growing Cell Structure Approach to Learning Case Retrieval Structures.- 7. An Architecture for Hybrid Creative Reasoning.- 8. Teacher: A Genetics Based System for Learning and Generalizing Heuristics.- Neuro-Fuzzy Computing.- 9. Fuzzy Logic Based Neural Network for Case Based Reasoning.- 10. Case Based Systems: A Neuro-Fuzzy Method for Selecting Cases.- 11. Neuro-Fuzzy Approach for Maintaining Case Bases.- 12. A Neuro-Fuzzy Methodology for Case Retrieval and an Object-Oriented Case Schema for Structuring Case Bases and their Applicationto Fashion Footwear Design.- Applications.- 13. Adaptation of Cases for Case Based Forecasting with Neural Network Support.- 14. Armchair Mission to Mars: Using Case Based Reasoning and Fuzzy Logic to Simulate a Time Series Model of Astronaut Crews.- 15. Applications of Soft CBR at General Electric.- About the Editors.
