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Modeling Uncertainty with Fuzzy Logic [electronic resource] : With Recent Theory and Applications / by Asli Celikyilmaz, I. Burhan Tȭrksen.

Por: Celikyilmaz, Asli [author.]Colaborador(es): Tȭrksen, I. Burhan [author.]Tipo de material: TextoTextoSeries Studies in Fuzziness and Soft Computing, 240Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Descripción: XLVIII, 400 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783540899242Trabajos contenidos: SpringerLink (Online service)Tema(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)Formatos físicos adicionales: Sin títuloClasificación CDD: 519 Clasificación LoC:TA329-348TA640-643Recursos en línea: de clik aquí para ver el libro electrónico
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Springer eBooksResumen: The objective of this book is to present an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". Since most researchers on fuzzy systems are more familiar with the standard fuzzy rule bases and their inference system structures, many standard tools of fuzzy system modeling approaches are reviewed to demonstrate the novelty of the structurally different fuzzy functions, before we introduced the new methodologies. To make the discussions more accessible, no special fuzzy logic and system modeling knowledge is assumed. Therefore, the book itself may be a reference for some related methodologies to most researchers on fuzzy systems analyses. For those readers, who have knowledge of essential fuzzy theories, Chapter 1, 2 should be treated as a review material. Advanced readers ought to be able to read chapters 3, 4 and 5 directly, where proposed methods are presented. Chapter 6 demonstrates experiments conducted on various datasets.
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Fuzzy Sets and Systems -- Improved Fuzzy Clustering -- Fuzzy Functions Approach -- Modeling Uncertainty with Improved Fuzzy Functions -- Experiments -- Conclusions and Future Work.

The objective of this book is to present an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". Since most researchers on fuzzy systems are more familiar with the standard fuzzy rule bases and their inference system structures, many standard tools of fuzzy system modeling approaches are reviewed to demonstrate the novelty of the structurally different fuzzy functions, before we introduced the new methodologies. To make the discussions more accessible, no special fuzzy logic and system modeling knowledge is assumed. Therefore, the book itself may be a reference for some related methodologies to most researchers on fuzzy systems analyses. For those readers, who have knowledge of essential fuzzy theories, Chapter 1, 2 should be treated as a review material. Advanced readers ought to be able to read chapters 3, 4 and 5 directly, where proposed methods are presented. Chapter 6 demonstrates experiments conducted on various datasets.

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