Soft Computing in Case Based Reasoning
| PUBLISHER | Springer (10/16/2000) |
| PRODUCT TYPE | Paperback (Paperback) |
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.
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Product Format
Product Details
ISBN-13:
9781852332624
ISBN-10:
185233262X
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
More Product Details
Page Count:
372
Carton Quantity:
22
Product Dimensions:
6.14 x 0.81 x 9.21 inches
Weight:
1.22 pound(s)
Feature Codes:
Illustrated
Country of Origin:
US
Subject Information
BISAC Categories
Computers | Intelligence (AI) & Semantics
Computers | Electrical
Dewey Decimal:
006.3
Library of Congress Control Number:
00032973
Descriptions, Reviews, Etc.
publisher marketing
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.
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Editor:
Dillon, Tharam S.
Tharam S. Dillon received his Ph.D. from Monash University. He is Professor of Computing at Hong Kong Polytechnic University. He is a Fellow of the IEEE, a Fellow of the Institution of Engineers (Australia), a Fellow of the Safety and Reliability Society (UK) and a Fellow of the Australian Computer Society. He has published over 400 technical articles and is a consultant for several corporations.
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