The case-based reasoning (CBR) and case-based design (CBD) have been around for some time and established themselves as one of the commonly used mechanisms of approximate reasoning in intelligent systems and de- sion support systems, in particular. In a nutshell, the CBR mechanisms o?er a powerful and general environment in which we generalize on a basis of - ready accumulated experience being represented in the form of a ?nite and relatively small collection of cases. Those cases constitute the essence of the existing domain knowledge. When encountering a new situation we invoke and eventually modify the already collected decision scenarios (cases) and arrive at the pertinent decision or a certain design alternative. Interestingly, uncertainty or granularity of resulting decision is inherently associated with the nature of the cases being used in the reasoning process and a way in which partial matching takes place between the historical ?ndings (cases) and a current evidence. ThebookbyProfessorsAvramenkoandKraslawskiisuniqueinseveral- portant ways. First, it is an impressive and in-depth treatment of the essence of the case-based reasoning strategy and case-based design dwelling upon the algorithmic facet of the paradigm. Second, the authors provided an excellent applied research framework by showing how this development can be e?- tivelyutilizedinrealwordcomplicatedenvironmentofprocessengineering–a pursuit that is rarely reported in the literature in such a comprehensive m- ner as done in this book.
| ISBN-13: | 9783540757054 |
| ISBN-10: | 3540757058 |
| Publisher: | Springer Science & Business Media |
| Publication date: | 2008-01-21 |
| Edition description: | 2008 |
| Pages: | 181 |
| Product dimensions: | Height: 9.75 Inches, Length: 6.25 Inches, Weight: 1.0251495183 Pounds, Width: 0.5 Inches |
| Author: | Yuri Avramenko, Andrzej Kraslawski |
| Language: | en |
| Binding: | Hardcover |
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