uncertain rule based fuzzy systems von mendel jerry (15 Ergebnisse)

Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: Good. 1st. Used book that is in clean, average condition without any missing pages.

Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.

Hardcover. Zustand: Brand New. 2nd edition. 684 pages. 9.25x6.25x1.50 inches. In Stock.

Hardcover. Zustand: As New. 2. Auflage. Like new. Immediately dispatched from Germany.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New.

Zustand: New.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The third edition of this textbook presents a further updated approach to fuzzy sets and systems that can model uncertainty - i.e., 'type-2' fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications, from time-series forecasting to knowledge mining to classification to control and to explainable AI (XAI). This latest edition again begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty, leading to type-2 fuzzy sets and systems. New material is included about how to obtain fuzzy set word models that are needed for XAI, similarity of fuzzy sets, a quantitative methodology that lets one explain in a simple way why the different kinds of fuzzy systems have the potential for performance improvements over each other, and new parameterizations of membership functions that have the potential for achieving even greater performance for all kinds of fuzzy systems. For hands-on experience, the book provides information on accessing MATLAB, Java, and Python software to complement the content. The book features a full suite of classroom material.

Zustand: Very good.

Buch. Zustand: Neu. Neuware -The third edition of this textbook presents a further updated approach to fuzzy sets and systems that can model uncertainty ¿ i.e., ¿type-2¿ fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications, from time-series forecasting to knowledge mining to classification to control and to explainable AI (XAI). This latest edition again begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty, leading to type-2 fuzzy sets and systems. New material is included about how to obtain fuzzy set word models that are needed for XAI, similarity of fuzzy sets, a quantitative methodology that lets one explain in a simple way why the different kinds of fuzzy systems have the potential for performance improvements over each other, and new parameterizations of membership functions that have the potential for achieving even greater performance for all kinds of fuzzy systems. For hands-on experience, the book provides information on accessing MATLAB, Java, and Python software to complement the content. The book features a full suite of classroom material.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 604 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty ¿ i.e., ¿type-2¿ fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems ¿ from type-1 to interval type-2 to general type-2 ¿ in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 708 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty - i.e., 'type-2' fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems-from type-1 to interval type-2 to general type-2 - in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The third edition of this textbook presents a further updated approach to fuzzy sets and systems that can model uncertainty - i.e., 'type-2' fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications, from time-series forecasting to knowledge mining to classification to control and to explainable AI (XAI). This latest edition again begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty, leading to type-2 fuzzy sets and systems. New material is included about how to obtain fuzzy set word models that are needed for XAI, similarity of fuzzy sets, a quantitative methodology that lets one explain in a simple way why the different kinds of fuzzy systems have the potential for performance improvements over each other, and new parameterizations of membership functions that have the potential for achieving even greater performance for all kinds of fuzzy systems. For hands-on experience, the book provides information on accessing MATLAB, Java, and Python software to complement the content. The book features a full suite of classroom material.