Uncertain Rule-Based Fuzzy Systems

Introduction and New Directions, 2nd Edition

Author: Jerry M. Mendel

Publisher: Springer

ISBN: 3319513702

Category: Technology & Engineering

Page: 684

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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.
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Uncertain Rule-based Fuzzy Logic Systems

Introduction and New Directions

Author: Jerry M. Mendel

Publisher: Prentice Hall

ISBN: 9780130409690

Category: Computers

Page: 555

View: 6025

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Preface Uncertainty is the fabric that makes life interesting. For millenia human beings have developed strategies to cope with a plethora of uncertainties, never absolutely sure what the consequences would be, but hopeful that the deleterious effects of those uncertainties could be minimized. This book presents a complete methodology for accomplishing this within the framework of fuzzy logic (FL). This is not the original FL, but is an expanded and richer FL, one that contains the original FL within it. The original FL, founded by Lotfi Zadeh, has been around for more than 35 years, as of the year 2000, and yet it is unable to handle uncertainties. Byhandle, I meanto model and minimize the effect of. That the original FL—type-1 FL—cannot do this sounds paradoxical because the word fuzzy has the connotation of uncertainty. The expanded FL—type-2 FL—is able to handle uncertainties because it can model them and minimize their effects. And, if all uncertainties disappear, type-2 FL reduces to type-1 FL, in much the same way that if randomness disappears, probability reduces to determinism. Although many applications were found for type-1 FL, it is its application torule-based systemsthat has most significantly demonstrated its importance as a powerful design methodology. Such rule-based fuzzy logic systems (FLSs), both type-1 and type-2, are what this book is about. In it I show how to use FL in new ways and how to effectively solve problems that are awash in uncertainties. FL has already been applied in numerous fields, in many of which uncertainties are present (e.g., signal processing, digital communications, computer and communication networks, diagnostic medicine, operations research, financial investing, control, etc.). Hence, the results in this book can immediately be used in all of these fields. To demonstrate the performance advantages for type-2 FLSs over their type-1 counterparts, when uncertainties are present, I describe and provide results for the following applications in this book: forecasting of time series, knowledge-mining using surveys, classification of video data working directly with compressed data, equalization of time-varying nonlinear digital communication channels, overcoming co-channel interference and intersymbol interference for time-varying nonlinear digital communication channels, and connection admission control for asynchronous transfer mode networks. No control applications have been included, because to date type-2 FL has not yet been applied to them; hence, this book is not about FL control, although its methodologies may someday be applicable to it. I have organized this book into four parts. Part 1—Preliminaries— contains four chapters that provide background materials about uncertainty, membership functions, and two case studies (forecasting of time-series and knowledge mining using surveys) that are carried throughout the book. Part 2—Type-1 Fuzzy Logic Systems—contains two chapters that are included to provide the underlying basis for the new type-2 FLSs, so that we can compare type-2 results for our case studies with type-1 results. Part 3—Type-2 Fuzzy Sets—contains three chapters, each of which focuses on a different aspect of such sets. Part 4—Type-2 Fuzzy Logic Systems—which is the heart of the book, contains five chapters, four having to do with different architectures for a FLS and how to handle different kinds of uncertainties within them, and one having to do primarily with four specific applications of type-2 FLSs. This book can be read by anyone who has an undergraduate BS degree and should be of great interest to computer scientists and engineers who already use or want to use rule-based systems and are concerned with how to handle uncertainties about such systems. I have included many worked-out examples in the text, and have also included homework problems at the end of most chapters so that the book can be used in a classroom setting as well as a technical reference. Here are some specific ways that this book can be used: For the person totally unfamiliar with FL who wants a quick introduction to it, read the Supplement to Chapter 1 and Chapter 5 (Sections 5.1-5.8). For the person who wants an in-depth treatment of type-1 rule-based FLSs, read the Supplement to Chapter 1 and Chapters 4-6. For the person who is only interested in type-2 fuzzy set theory, read Chapters 3, 7-9, and Appendices A and B. For a person who wants to give a course on rule-based fuzzy logic systems, use Chapters 1-12 and 13 (if time permits). Chapter 14 should be of interest to people with a background in digital communications, pattern recognition, or communication networks and will suggest projects for a course. For a person who is a proponent of Takagi-Sugeno-Kang (TSK) fuzzy systems and wants to see what their type-2 counterparts look like, read Chapters 3, 7-9, and 13. For a person who is interested in forecasting of time-series and wants to get a quick overview of the benefits to modeling uncertainties on forecasting performance when using rule-based forecasters, read Chapters 4 (Section 4.2), 5 (Section 5.10), 6 (Section 6.7), 10 (Section 10.11), 11 (Section 11.5), and 12 (Section 12.5). For a person who is interested in knowledge mining and wants to get a quick overview of the benefits to modeling uncertainties on judgment making when using rule-based advisors, read Chapters 4 (Section 4.3), 5 (Section 5.11), and 10 (Section 10.12). So that people will start using type-2 FL as soon as possible, I have made free software available online for implementing and designing type-1 and type-2 FLSs. It is MATLAB-based (MATLAB is a registered trademark of The MathWorks, Inc.), was developed by my former PhD students Nilesh Karnik and Qilian Liang, and can be reached at:http://sipi.usc.edu/. A computation section, which directs the reader to very specific M-files, appears at the end of most chapters of this book. Appendix C summarizes all of the M-files so that the reader can see the forest from the trees.
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Fuzzy Information and Engineering

Author: Bingyuan Cao,Tai-Fu Li,Cheng-Yi Zhang

Publisher: Springer Science & Business Media

ISBN: 9783642036644

Category: Mathematics

Page: 1754

View: 9228

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This book is the proceedings of the Third International Conference on Fuzzy Information and Engineering (ICFIE 2009) held in the famous mountain city Chongqing in Southwestern China, from September 26-29, 2009. Only high-quality papers are included. The ICFIE 2009, built on the success of previous conferences, the ICFIE 2007 (Guangzhou, China), is a major symposium for scientists, engineers and practitioners in the world to present their updated results, ideas, developments and applications in all areas of fuzzy information and engineering. It aims to strengthen relations between industry research laboratories and universities, and to create a primary symposium for world scientists in fuzzy fields as follows: Fuzzy Information; Fuzzy Sets and Systems; Soft Computing; Fuzzy Engineering; Fuzzy Operation Research and Management; Artificial Intelligence; Fuzzy Mathematics and Systems in Applications, etc.
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Advances in Type-2 Fuzzy Sets and Systems

Theory and Applications

Author: Alireza Sadeghian,Jerry M Mendel,Hooman Tahayori

Publisher: Springer

ISBN: 1461466660

Category: Computers

Page: 262

View: 1715

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This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet. The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.
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Fuzzy Systems: Concepts, Methodologies, Tools, and Applications

Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

ISBN: 1522519092

Category: Mathematics

Page: 1765

View: 1044

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There are a myriad of mathematical problems that cannot be solved using traditional methods. The development of fuzzy expert systems has provided new opportunities for problem-solving amidst uncertainties. Fuzzy Systems: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source on the latest scholarly research and developments in fuzzy rule-based methods and examines both theoretical foundations and real-world utilization of these logic sets. Featuring a range of extensive coverage across innovative topics, such as fuzzy logic, rule-based systems, and fuzzy analysis, this is an essential publication for scientists, doctors, engineers, physicians, and researchers interested in emerging perspectives and uses of fuzzy systems in various sectors.
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MICAI 2009: Advances in Artificial Intelligence

8th Mexican International Conference on Artificial Intelligence, Guanajuato, México, November 9-13, 2009 Proceedings

Author: Arturo Hernández Aguirre,Raúl Monroy Borja,Carlos Albetro Reyes García

Publisher: Springer Science & Business Media

ISBN: 3642052576

Category: Computers

Page: 743

View: 7913

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This book constitutes the refereed proceedings of the 8th Mexican International Conference on Artificial Intelligence, MICAI 2009, held in Guanajuato, Mexico, in November 2009. The 63 revised full papers presented together with one invited talk were carefully reviewed and selected from 215 submissions. The papers are organized in topical sections on logic and reasoning, ontologies, knowledge management and knowledge-based systems, uncertainty and probabilistic reasoning, natural language processing, data mining, machine learning, pattern recognition, computer vision and image processing, robotics, planning and scheduling, fuzzy logic, neural networks, intelligent tutoring systems, bioinformatics and medical applications, hybrid intelligent systems and evolutionary algorithms.
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Fuzzy Information Processing

37th Conference of the North American Fuzzy Information Processing Society, NAFIPS 2018, Fortaleza, Brazil, July 4-6, 2018, Proceedings

Author: Guilherme A. Barreto,Ricardo Coelho

Publisher: Springer

ISBN: 3319953125

Category: Computers

Page: 602

View: 8977

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This book constitutes the thoroughly refereed proceedings of the 37th IFSA Conference, NAFIPS 2018, held in Fortaleza, Brazil, in July 2018. The 55 full papers presented were carefully reviewed and selected from 73 submissions. The papers deal with a large spectrum of topics, including theory and applications of fuzzy numbers and sets, fuzzy logic, fuzzy inference systems, fuzzy clustering, fuzzy pattern classification, neuro-fuzzy systems, fuzzy control systems, fuzzy modeling, fuzzy mathematical morphology, fuzzy dynamical systems, time series forecasting, and making decision under uncertainty.
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Modelling of an Interval Type-2 Fussy Logic System (IT2 FLS) on Continuous Domain with Medical Application

Author: R.W. Hndoosh,M.S. Saroa,S. Kumar

Publisher: GRIN Verlag

ISBN: 3656942277

Category: Computers

Page: 13

View: 6789

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Academic Paper from the year 2015 in the subject Computer Science - Applied, , course: ph.d, language: English, abstract: An overview and a derivation of interval type-2 fussy logic system (IT2 FLS), which can handle rule’s uncertainties on continuous domain, having good number of applications in real world. This work fo-cused on the performance of an IT2 FLS that involves the operations of a fuzzification, inference, and output processing. The output processing consists of Type-Reduction (TR) and defuzzification. This work made IT2 FLS much more accessible to FLS modellers, because it provides mathematical formulation for calculating the de-rivatives. Presenting extend to representation of T2 FSs on continuous domain and using it to derive formulas for operations, we developed and extended the derivation of the union of two IT2 FSs to the derivation of the intersection and union of N-IT2 FSs that is based on various concepts. The derivation of all the formulas that are related with an IT2 and these formulas depend on continuous domain with multiple rules. Each rule has multiple antecedents that are activated by a crisp number with T2 singleton fuzzification (SF). Then, we have shown how those results can be extended to T2 non-singleton fuzzification (NSF). We are derived the relation-ship between the consequent and the domain of uncertainty (DOU) of the T2 fired output FS. As well as, provide the derivation of the general form at continuous domain to calculate the different kinds of type-reduced. We have also applied an IT2 FLS to medical application of Heart Diseases (HDs) and an IT2 provide rather modest performance improvements over the T1 predictor. Finally, we made a comparison of HDs result between IT2 FLS using the IT2FLS in MATLAB and the IT2 FLS in Visual C# models with T1 FISs (Mamdani, and Takagi-Sugeno).
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Smart Systems Engineering

Infra-structure Systems Engineering, Bio-informatics and Computational Biology and Evolutionary Computation : Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE 2006) : Held November 6-8, 2006, in St. Louis, Missouri, U.S.A.

Author: Cihan H. Dagli

Publisher: Amer Society of Mechanical

ISBN: 9780791802564

Category: Computers

Page: 857

View: 3986

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