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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
In a highly authoritative and systematic manner, this book offers an in-depth treatment of the essence of the case-based reasoning strategy and case-based design dwelling upon the algorithmic facet of the paradigm. It provides an excellent applied research framework by showing how this development can be effectively utilized in the real word complicated environment of process engineering, a pursuit that is rarely reported in the literature in such a comprehensive manner.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783540757054
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