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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 applications from...
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Lenguaje: | eng |
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Springer
2017
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Acceso en línea: | https://dx.doi.org/10.1007/978-3-319-51370-6 http://cds.cern.ch/record/2267207 |
_version_ | 1780954566145081344 |
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author | Mendel, Jerry M |
author_facet | Mendel, Jerry M |
author_sort | Mendel, Jerry M |
collection | CERN |
description | 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. |
id | cern-2267207 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2017 |
publisher | Springer |
record_format | invenio |
spelling | cern-22672072021-04-21T19:12:30Zdoi:10.1007/978-3-319-51370-6http://cds.cern.ch/record/2267207engMendel, Jerry MUncertain rule-based fuzzy systems: introduction and new directionsEngineeringThe 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.Springeroai:cds.cern.ch:22672072017 |
spellingShingle | Engineering Mendel, Jerry M Uncertain rule-based fuzzy systems: introduction and new directions |
title | Uncertain rule-based fuzzy systems: introduction and new directions |
title_full | Uncertain rule-based fuzzy systems: introduction and new directions |
title_fullStr | Uncertain rule-based fuzzy systems: introduction and new directions |
title_full_unstemmed | Uncertain rule-based fuzzy systems: introduction and new directions |
title_short | Uncertain rule-based fuzzy systems: introduction and new directions |
title_sort | uncertain rule-based fuzzy systems: introduction and new directions |
topic | Engineering |
url | https://dx.doi.org/10.1007/978-3-319-51370-6 http://cds.cern.ch/record/2267207 |
work_keys_str_mv | AT mendeljerrym uncertainrulebasedfuzzysystemsintroductionandnewdirections |