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Añadir al carritoCondición: New. pp. 448.
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Fuzzy Cognitive Maps | Advances in Theory, Methodologies, Tools and Applications | Michael Glykas | Taschenbuch | Studies in Fuzziness and Soft Computing | 200 S. | Englisch | 2012 | Springer | EAN 9783642263989 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2012
ISBN 10: 3642263984 ISBN 13: 9783642263989
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,49
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This important edited volume is the first such book ever published on fuzzy cognitive maps (FCMs). Professor Michael Glykas has done an exceptional job in bringing together and editing its seventeen chapters. The volume appears nearly a quarter century after my original article 'Fuzzy Cognitive Maps' appeared in the International Journal of Man-Machine Studies in 1986. The volume accordingly reflects many years of research effort in the development of FCM theory and applications-and portends many more decades of FCM research and applications to come. FCMs are fuzzy feedback models of causality. They combine aspects of fuzzy logic, neural networks, semantic networks, expert systems, and nonlinear dynamical systems. That rich structure endows FCMs with their own complexity and lets them apply to a wide range of problems in engineering and in the soft and hard sciences. Their partial edge connections allow a user to directly represent causality as a matter of degree and to learn new edge strengths from training data. Their directed graph structure allows forward or what-if inferencing. FCM cycles or feedback paths allow for complex nonlinear dynamics. Control of FCM nonlinear dynamics can in many cases let the user encode and decode concept patterns as fixed-point attractors or limit cycles or perhaps as more exotic dynamical equilibria. These global equilibrium patterns are often 'hidden' in the nonlinear dynamics. The user will not likely see these global patterns by simply inspecting the local causal edges or nodes of large FCMs.
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Añadir al carritoPaperback. Condición: Brand New. 2010 edition. 200 pages. 9.20x6.10x1.01 inches. In Stock.
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Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg Sep 2012, 2012
ISBN 10: 3642263984 ISBN 13: 9783642263989
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 160,49
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This important edited volume is the first such book ever published on fuzzy cognitive maps (FCMs). Professor Michael Glykas has done an exceptional job in bringing together and editing its seventeen chapters. The volume appears nearly a quarter century after my original article 'Fuzzy Cognitive Maps' appeared in the International Journal of Man-Machine Studies in 1986. The volume accordingly reflects many years of research effort in the development of FCM theory and applications-and portends many more decades of FCM research and applications to come. FCMs are fuzzy feedback models of causality. They combine aspects of fuzzy logic, neural networks, semantic networks, expert systems, and nonlinear dynamical systems. That rich structure endows FCMs with their own complexity and lets them apply to a wide range of problems in engineering and in the soft and hard sciences. Their partial edge connections allow a user to directly represent causality as a matter of degree and to learn new edge strengths from training data. Their directed graph structure allows forward or what-if inferencing. FCM cycles or feedback paths allow for complex nonlinear dynamics. Control of FCM nonlinear dynamics can in many cases let the user encode and decode concept patterns as fixed-point attractors or limit cycles or perhaps as more exotic dynamical equilibria. These global equilibrium patterns are often 'hidden' in the nonlinear dynamics. The user will not likely see these global patterns by simply inspecting the local causal edges or nodes of large FCMs. 448 pp. Englisch.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2012
ISBN 10: 3642263984 ISBN 13: 9783642263989
Librería: moluna, Greven, Alemania
EUR 136,16
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Contains the theory of fuzzy cognitive mapping and for the first time a methodology of constructing and linking fuzzy cognitive maps to be used in management and business process reengineering for performance measurement purposesContains a softwar.
Librería: Majestic Books, Hounslow, Reino Unido
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Añadir al carritoCondición: New. Print on Demand pp. 448.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 202,95
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 448.
Idioma: Inglés
Publicado por Springer, Springer Sep 2012, 2012
ISBN 10: 3642263984 ISBN 13: 9783642263989
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 160,49
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This important edited volume is the first such book ever published on fuzzy cognitive maps (FCMs). Professor Michael Glykas has done an exceptional job in bringing together and editing its seventeen chapters. The volume appears nearly a quarter century after my original article ¿Fuzzy Cognitive Maps¿ appeared in the International Journal of Man-Machine Studies in 1986. The volume accordingly reflects many years of research effort in the development of FCM theory and applications¿and portends many more decades of FCM research and applications to come. FCMs are fuzzy feedback models of causality. They combine aspects of fuzzy logic, neural networks, semantic networks, expert systems, and nonlinear dynamical systems. That rich structure endows FCMs with their own complexity and lets them apply to a wide range of problems in engineering and in the soft and hard sciences. Their partial edge connections allow a user to directly represent causality as a matter of degree and to learn new edge strengths from training data. Their directed graph structure allows forward or what-if inferencing. FCM cycles or feedback paths allow for complex nonlinear dynamics. Control of FCM nonlinear dynamics can in many cases let the user encode and decode concept patterns as fixed-point attractors or limit cycles or perhaps as more exotic dynamical equilibria. These global equilibrium patterns are often ¿hidden¿ in the nonlinear dynamics. The user will not likely see these global patterns by simply inspecting the local causal edges or nodes of large FCMs.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 448 pp. Englisch.