Type 2 Fuzzy Logic Theory and Applications

This book is intended to be a major reference tool and can be used as a textbook. This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing techniques.

Type 2 Fuzzy Logic  Theory and Applications

This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing (SC) techniques. The authors extend the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. This book is intended to be a major reference tool and can be used as a textbook.

Type 2 Fuzzy Neural Networks and Their Applications

Aliev RA, Tserkovny AE (2011) A systemic approach to fuzzy logic formalization
for approximate reasoning. Information Sciences, 181 ... Springer, USA. Castillo
O, Melin P (2008) Type-2 fuzzy logic: Theory and applications. Springer ...

Type 2 Fuzzy Neural Networks and Their Applications

This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination with other paradigms of Soft Computing technology such as Neuro-Computing and Evolutionary Computing. It provides a self-contained exposition of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making, system identification and other real problems. Type-2 Fuzzy Neural Networks and Their Applications is helpful for teachers and students of universities and colleges, for scientists and practitioners from various fields such as control, decision analysis, pattern recognition and similar fields.

Intuitionistic and Type 2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms Theory and Applications

This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern ...

Intuitionistic and Type 2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms  Theory and Applications

This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The topic is highly relevant as most current intelligent systems and devices use some form of intelligent feature to enhance their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which are of great interest to researchers in these areas. Further, it proposes novel, nature-inspired optimization algorithms and innovative neural models. Featuring contributions on theoretical aspects as well as applications, the book appeals to a wide audience.

Fuzzy Logic Theory and Applications

union, intersection and complement of Type-2 fuzzy sets A and B can be defined
as follows [235): Union: AU Be unus(r) ... A t-norm can be extended to be a
conjunction in Type2 logic and an intersection in Type-2 fuzzy set theory, such as
a ...

Fuzzy Logic Theory and Applications

Nowadays, voluminous textbooks and monographs in fuzzy logic are devoted only to separate or some combination of separate facets of fuzzy logic. There is a lack of a single book that presents a comprehensive and self-contained theory of fuzzy logic and its applications. Written by world renowned authors, Lofti Zadeh, also known as the Father of Fuzzy Logic, and Rafik Aliev, who are pioneers in fuzzy logic and fuzzy sets, this unique compendium includes all the principal facets of fuzzy logic such as logical, fuzzy-set-theoretic, epistemic and relational. Theoretical problems are prominently illustrated and illuminated by numerous carefully worked-out and thought-through examples. This invaluable volume will be a useful reference guide for academics, practitioners, graduates and undergraduates in fuzzy logic and its applications.

Advances in Type 2 Fuzzy Sets and Systems

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 ...

Advances in Type 2 Fuzzy Sets and Systems

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.

Introduction To Type 2 Fuzzy Logic Control

The book includes worked examples, experiment and simulation results, and comprehensive reference materials. The book also offers downloadable computer programs from an associated website.

Introduction To Type 2 Fuzzy Logic Control

An introductory book that provides theoretical, practical,and application coverage of the emerging field of type-2 fuzzylogic control Until recently, little was known about type-2 fuzzy controllersdue to the lack of basic calculation methods available for type-2fuzzy sets and logic—and many different aspects of type-2fuzzy control still needed to be investigated in order to advancethis new and powerful technology. This self-contained referencecovers everything readers need to know about the growing field. Written with an educational focus in mind, Introduction toType-2 Fuzzy Logic Control: Theory and Applications uses acoherent structure and uniform mathematical notations to linkchapters that are closely related, reflecting the book’scentral themes: analysis and design of type-2 fuzzy controlsystems. The book includes worked examples, experiment andsimulation results, and comprehensive reference materials. The bookalso offers downloadable computer programs from an associatedwebsite. Presented by world-class leaders in type-2 fuzzy logic control,Introduction to Type-2 Fuzzy Logic Control: Is useful for any technical person interested in learningtype-2 fuzzy control theory and its applications Offers experiment and simulation results via downloadablecomputer programs Features type-2 fuzzy logic background chapters to make thebook self-contained Provides an extensive literature survey on both fuzzy logic andrelated type-2 fuzzy control Introduction to Type-2 Fuzzy Logic Control is aneasy-to-read reference book suitable for engineers, researchers,and graduate students who want to gain deep insight into type-2fuzzy logic control.

Type 2 Fuzzy Logic in Intelligent Control Applications

Information Sciences 181, 1591–1608 (2011) Al-Jaafreh, M.O., Al-Jumaily, A.A.:
Training type-2 fuzzy system by particle swarm optimization. In: IEEE ... 163–178
(2008) Castillo, O., Melin, P.: Type-2 Fuzzy Logic: Theory and Applications.

Type 2 Fuzzy Logic in Intelligent Control Applications

We describe in this book, hybrid intelligent systems based mainly on type-2 fuzzy logic for intelligent control. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. The book is organized in three main parts, which contain a group of chapters around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which can be the basis for achieving intelligent control with interval type-2 fuzzy logic. The second part of the book is comprised of chapters with the main theme of evolutionary optimization of type-2 fuzzy systems in intelligent control with the aim of designing optimal type-2 fuzzy controllers for complex control problems in diverse areas of application, including mobile robotics, aircraft dynamics systems and hardware implementations. The third part of the book is formed with chapters dealing with the theme of bio-inspired optimization of type-2 fuzzy systems in intelligent control, which includes the application of particle swarm intelligence and ant colony optimization algorithms for obtaining optimal type-2 fuzzy controllers.

Analysis and Design of Intelligent Systems Using Soft Computing Techniques

Soft Computing (SC) consists of several computing paradigms, including fuzzy
logic, neural networks, and genetic ... papers on “Type-2 Fuzzy Logic: theory and
applications” that describe different contributions to the theory of type-2 fuzzy
logic ...

Analysis and Design of Intelligent Systems Using Soft Computing Techniques

This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.

Interval Neutrosophic Sets and Logic Theory and Applications in Computing

Theory and Applications in Computing Haibin Wang, Florentin Smarandache,
Rajshekhar Sunderraman, Yan-Qing Zhang. Chapter 2 Interval Neutrosophic
Logic In this chapter, we present a novel interval neutrosophic logic that
generalizes the interval valued fuzzy logic, the intuitionistic fuzzy logic and ...
There are related works such as type-2 fuzzy sets and type-2 fuzzy logic [KM98,
LM00, M302].

Interval Neutrosophic Sets and Logic  Theory and Applications in Computing

This book presents the advancements and applications of neutrosophics, which are generalizations of fuzzy logic, fuzzy set, and imprecise probability. The neutrosophic logic, neutrosophic set, neutrosophic probability, and neutrosophic statistics are increasingly used in engineering applications (especially for software and information fusion), medicine, military, cybernetics, physics.In the last chapter a soft semantic Web Services agent framework is proposed to facilitate the registration and discovery of high quality semantic Web Services agent. The intelligent inference engine module of soft semantic Web Services agent is implemented using interval neutrosophic logic.

Knowledge Based Neurocomputing A Fuzzy Logic Approach

222. James J. Buckley, Leonard J. Jowers Monte Carlo Methods in Fuzzy
Optimization, 2008 ISBN 978-3-540-76289-8 Vol. 223. Oscar Castillo, Patricia
Melin Type-2 Fuzzy Logic: Theory and Applications, 2008 ISBN 978-3-540-
76283-6 Vol.

Knowledge Based Neurocomputing  A Fuzzy Logic Approach

We do not perceive the present as it is and in totality, nor do we infer the future from the present with any high degree of dependability, nor yet do we accurately know the consequences of our own actions. In addition, there is a fourth source of error to be taken into account, for we do not execute actions in the precise form in which they are imaged and willed. Frank H. Knight R4.34, p. 202] The degree of certainty of confidence felt in the conclusion after it is reached cannot be ignored, for it is of the greatest practical signi- cance. The action which follows upon an opinion depends as much upon the amount of confidence in that opinion as it does upon fav- ableness of the opinion itself. The ultimate logic, or psychology, of these deliberations is obscure, a part of the scientifically unfathomable mystery of life and mind. Frank H. Knight R4.34, p. 226-227] With some inaccuracy, description of uncertain consequences can be classified into two categories, those which use exclusively the language of probability distributions and those which call for some other principle, either to replace or supplement."