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Uncertain rule-based fuzzy systems =...

Mendel, Jerry M.

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Uncertain rule-based fuzzy systems = introduction and new birections /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Uncertain rule-based fuzzy systems/ by Jerry M. Mendel.
Reminder of title:	introduction and new birections /
Author:	Mendel, Jerry M.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xxii, 684 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introduction -- Part 1: Type-1 Fuzzy Sets and Systems -- Short Primers on Type-1 Fuzzy Sets and Fuzzy Logic -- Type-1 Fuzzy Logic Systems -- Part 2: Type-2 Fuzzy Sets -- Sources of Uncertainty -- Type-2 Fuzzy Sets -- Operations on and Properties OF Type-2 Fuzzy Sets -- Type-2 Relations and Compositions -- Centroid of a Type-2 Fuzzy Set: Type-Reduction -- Part 3: Type-2 Fuzzy Logic Systems -- Mamdani Interval Type-2 Fuzzy Logic Systems (IT2 FLSS) -- TSK Interval Type-2 Fuzzy Logic Systems -- General Type-2 Fuzzy Logic Systems (GT2 FLSS) -- Conclusion.
Contained By:	Springer eBooks
Subject:	Fuzzy systems. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-51370-6
ISBN:	9783319513706

Uncertain rule-based fuzzy systems = introduction and new birections /
Mendel, Jerry M.

Uncertain rule-based fuzzy systemsintroduction and new birections /[electronic resource] :by Jerry M. Mendel. - 2nd ed. - Cham :Springer International Publishing :2017. - xxii, 684 p. :ill. (some col.), digital ;24 cm.

Introduction -- Part 1: Type-1 Fuzzy Sets and Systems -- Short Primers on Type-1 Fuzzy Sets and Fuzzy Logic -- Type-1 Fuzzy Logic Systems -- Part 2: Type-2 Fuzzy Sets -- Sources of Uncertainty -- Type-2 Fuzzy Sets -- Operations on and Properties OF Type-2 Fuzzy Sets -- Type-2 Relations and Compositions -- Centroid of a Type-2 Fuzzy Set: Type-Reduction -- Part 3: Type-2 Fuzzy Logic Systems -- Mamdani Interval Type-2 Fuzzy Logic Systems (IT2 FLSS) -- TSK Interval Type-2 Fuzzy Logic Systems -- General Type-2 Fuzzy Logic Systems (GT2 FLSS) -- Conclusion.

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. Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties; Allows those already familiar with type-1 fuzzy sets and systems to rapidly come up to speed to type-2 fuzzy sets and systems; Features complete classroom material including end-of-chapter exercises, a solutions manual, and three case studies -- forecasting of time series to knowledge mining from surveys and PID control.

ISBN: 9783319513706

Standard No.: 10.1007/978-3-319-51370-6doiSubjects--Topical Terms:

535881
Fuzzy systems.

LC Class. No.: QA402

Dewey Class. No.: 511.313

Uncertain rule-based fuzzy systems = introduction and new birections /
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245 1 0 $a Uncertain rule-based fuzzy systems $h [electronic resource] : $b introduction and new birections / $c by Jerry M. Mendel.
250 $a 2nd ed.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xxii, 684 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Introduction -- Part 1: Type-1 Fuzzy Sets and Systems -- Short Primers on Type-1 Fuzzy Sets and Fuzzy Logic -- Type-1 Fuzzy Logic Systems -- Part 2: Type-2 Fuzzy Sets -- Sources of Uncertainty -- Type-2 Fuzzy Sets -- Operations on and Properties OF Type-2 Fuzzy Sets -- Type-2 Relations and Compositions -- Centroid of a Type-2 Fuzzy Set: Type-Reduction -- Part 3: Type-2 Fuzzy Logic Systems -- Mamdani Interval Type-2 Fuzzy Logic Systems (IT2 FLSS) -- TSK Interval Type-2 Fuzzy Logic Systems -- General Type-2 Fuzzy Logic Systems (GT2 FLSS) -- Conclusion.
520 $a 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. Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties; Allows those already familiar with type-1 fuzzy sets and systems to rapidly come up to speed to type-2 fuzzy sets and systems; Features complete classroom material including end-of-chapter exercises, a solutions manual, and three case studies -- forecasting of time series to knowledge mining from surveys and PID control.
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