Uncertain rule-based fuzzy systems : introduction and new directions
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 applica...
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Main Author: | |
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Format: | eBook |
Language: | English |
Published: |
Cham, Switzerland :
Springer,
2017.
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Edition: | Second edition. |
Subjects: | |
ISBN: | 9783319513706 9783319513690 |
Physical Description: | 1 online resource (xxii, 684 pages) : illustrations (some color) |
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100 | 1 | |a Mendel, Jerry M., |d 1938- |e author. | |
245 | 1 | 0 | |a Uncertain rule-based fuzzy systems : |b introduction and new directions / |c Jerry M. Mendel. |
250 | |a Second edition. | ||
264 | 1 | |a Cham, Switzerland : |b Springer, |c 2017. | |
300 | |a 1 online resource (xxii, 684 pages) : |b illustrations (some color) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a počítač |b c |2 rdamedia | ||
338 | |a online zdroj |b cr |2 rdacarrier | ||
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. | |
506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty | ||
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. | ||
590 | |a SpringerLink |b Springer Complete eBooks | ||
650 | 0 | |a Fuzzy systems. | |
650 | 0 | |a Uncertainty (Information theory) | |
655 | 7 | |a elektronické knihy |7 fd186907 |2 czenas | |
655 | 9 | |a electronic books |2 eczenas | |
776 | 0 | 8 | |i Printed edition: |z 9783319513690 |
856 | 4 | 0 | |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-319-51370-6 |y Plný text |
992 | |c NTK-SpringerENG | ||
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