Fuzzy Systems and Data Mining IV

B. Bouchon-Meunier, M. Detyniecki, M. Lesot, C. Marsala, and M. Rifqi, Real-
World Fuzzy Logic Applications in Data Mining and Information Retrieval, in:
Fuzzy Logic A Spectrum of Theoretical and Practical Issues, Studies in Fuzziness
and ...

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Author: A.J. Tallón-Ballesteros

Publisher: IOS Press

ISBN: 9781614999270

Category: Computers

Page: 988

View: 469

Big Data Analytics is on the rise in the last years of the current decade. Data are overwhelming the computation capacity of high performance servers. Cloud, grid, edge and fog computing are a few examples of the current hype. Computational Intelligence offers two faces to deal with the development of models: on the one hand, the crisp approach, which considers for every variable an exact value and, on the other hand, the fuzzy focus, which copes with values between two boundaries. This book presents 114 papers from the 4th International Conference on Fuzzy Systems and Data Mining (FSDM 2018), held in Bangkok, Thailand, from 16 to 19 November 2018. All papers were carefully reviewed by program committee members, who took into consideration the breadth and depth of the research topics that fall within the scope of FSDM. The acceptance rate was 32.85% . Offering a state-of-the-art overview of fuzzy systems and data mining, the publication will be of interest to all those whose work involves data science.

Fuzzy Systems and Data Mining VI

[7] Martinez-Lopez F, Jorge C. Marketing intelligent systems for consumer
behavior modeling by a descriptive induction approach based on genetic fuzzy
systems. Industrial Marketing Management. 2009; 38: 714-731. [8] Ektay T,
Cengiz K.

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Author: A.J. Tallón-Ballesteros

Publisher: IOS Press

ISBN: 9781643681351

Category: Computers

Page: 812

View: 301

The interdisciplinary field of fuzzy logic encompass applications in the electrical, industrial, chemical and engineering realms as well as in areas of management and environmental issues, while data mining covers new approaches to big data, massive data, and scalable, parallel and distributed algorithms. This book presents papers from the 6th International Conference on Fuzzy Systems and Data Mining (FSDM 2020). The conference was originally due to be held from 13-16 November 2020 in Xiamen, China, but was changed to an online conference held on the same dates due to ongoing restrictions connected with the COVID-19 pandemic. The annual FSDM conference provides a platform for knowledge exchange between international experts, researchers academics and delegates from industry. This year, the committee received 316 submissions, of which 76 papers were selected for inclusion in the conference; an acceptance rate of 24%. The conference covers four main areas: fuzzy theory; algorithms and systems, which includes topics like stability; foundations and control; and fuzzy applications, which are widely used and cover various types of processing as well as hardware and architecture for big data and time series. Providing a current overview of research and developments in fuzzy logic and data mining, the book will be of interest to all those working in the field of data science.

Fuzzy Sets Fuzzy Logic and Fuzzy Systems

This book consists of selected papers written by the founder of fuzzy set theory, Lotfi A Zadeh.

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Author: Lotfi Asker Zadeh

Publisher: World Scientific

ISBN: 9810224214

Category: Computers

Page: 826

View: 330

This book consists of selected papers written by the founder of fuzzy set theory, Lotfi A Zadeh. Since Zadeh is not only the founder of this field, but has also been the principal contributor to its development over the last 30 years, the papers contain virtually all the major ideas in fuzzy set theory, fuzzy logic, and fuzzy systems in their historical context. Many of the ideas presented in the papers are still open to further development. The book is thus an important resource for anyone interested in the areas of fuzzy set theory, fuzzy logic, and fuzzy systems, as well as their applications. Moreover, the book is also intended to play a useful role in higher education, as a rich source of supplementary reading in relevant courses and seminars.The book contains a bibliography of all papers published by Zadeh in the period 1949-1995. It also contains an introduction that traces the development of Zadeh's ideas pertaining to fuzzy sets, fuzzy logic, and fuzzy systems via his papers. The ideas range from his 1965 seminal idea of the concept of a fuzzy set to ideas reflecting his current interest in computing with words ? a computing in which linguistic expressions are used in place of numbers.Places in the papers, where each idea is presented can easily be found by the reader via the Subject Index.

A Course in Fuzzy Systems and Control

Provides a comprehensive, self-tutorial course in fuzzy logic and its increasing role in control theory. It summarizes the important results of the field in a well-structured framework.

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Author: Li-Xin Wang

Publisher: Prentice Hall

ISBN: UOM:39015038173335

Category: Computers

Page: 424

View: 576

Provides a comprehensive, self-tutorial course in fuzzy logic and its increasing role in control theory. It summarizes the important results of the field in a well-structured framework.

Fuzzy Logic Knowledge Bases in Integrated Landscape Assessment

As discussed in the next section , however , newer forms of knowledge - based
representation , based on object models and fuzzy logic , substantially improve
the ability to model large , general problem domains such as ecosystem ...

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Author: Keith M. Reynolds

Publisher:

ISBN: MINN:31951D02996421C

Category: Ecological assessment (Biology)

Page: 24

View: 488

Fundamentals of Computational Intelligence

Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, ...

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Author: James M. Keller

Publisher: John Wiley & Sons

ISBN: 9781119214359

Category: Technology & Engineering

Page: 378

View: 303

Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

Fuzzy Systems Engineering

Now, this reader-friendly book presents an up-to-date approach to fuzzy systems engineering, covering concepts, design methodologies, and algorithms coupled with interpretation, analysis, and underlying engineering knowledge.

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Author: Witold Pedrycz

Publisher: John Wiley & Sons

ISBN: 0470168951

Category: Technology & Engineering

Page: 544

View: 220

A self-contained treatment of fuzzy systems engineering, offering conceptual fundamentals, design methodologies, development guidelines, and carefully selected illustrative material Forty years have passed since the birth of fuzzy sets, in which time a wealth of theoretical developments, conceptual pursuits, algorithmic environments, and other applications have emerged. Now, this reader-friendly book presents an up-to-date approach to fuzzy systems engineering, covering concepts, design methodologies, and algorithms coupled with interpretation, analysis, and underlying engineering knowledge. The result is a holistic view of fuzzy sets as a fundamental component of computational intelligence and human-centric systems. Throughout the book, the authors emphasize the direct applicability and limitations of the concepts being discussed, and historical and bibliographical notes are included in each chapter to help readers view the developments of fuzzy sets from a broader perspective. A radical departure from current books on the subject, Fuzzy Systems Engineering presents fuzzy sets as an enabling technology whose impact, contributions, and methodology stretch far beyond any specific discipline, making it applicable to researchers and practitioners in engineering, computer science, business, medicine, bioinformatics, and computational biology. Additionally, three appendices and classroom-ready electronic resources make it an ideal textbook for advanced undergraduate- and graduate-level courses in engineering and science.

Introduction to Neuro Fuzzy Systems

Fuzzy sets were introduced by Zadeh (1965) as a means of representing and manipulating data that was not precise, but rather fuzzy.

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Author: Robert Fuller

Publisher: Springer Science & Business Media

ISBN: 9783790818529

Category: Computers

Page: 289

View: 739

Fuzzy sets were introduced by Zadeh (1965) as a means of representing and manipulating data that was not precise, but rather fuzzy. Fuzzy logic pro vides an inference morphology that enables approximate human reasoning capabilities to be applied to knowledge-based systems. The theory of fuzzy logic provides a mathematical strength to capture the uncertainties associ ated with human cognitive processes, such as thinking and reasoning. The conventional approaches to knowledge representation lack the means for rep resentating the meaning of fuzzy concepts. As a consequence, the approaches based on first order logic and classical probablity theory do not provide an appropriate conceptual framework for dealing with the representation of com monsense knowledge, since such knowledge is by its nature both lexically imprecise and noncategorical. The developement of fuzzy logic was motivated in large measure by the need for a conceptual framework which can address the issue of uncertainty and lexical imprecision. Some of the essential characteristics of fuzzy logic relate to the following [242]. • In fuzzy logic, exact reasoning is viewed as a limiting case of ap proximate reasoning. • In fuzzy logic, everything is a matter of degree. • In fuzzy logic, knowledge is interpreted a collection of elastic or, equivalently, fuzzy constraint on a collection of variables. • Inference is viewed as a process of propagation of elastic con straints. • Any logical system can be fuzzified. There are two main characteristics of fuzzy systems that give them better performance für specific applications.

Proceedings of the IEEE Conference on Fuzzy Systems

[ 10 ] H . Ying , “ Sufficient conditions on general fuzzy systems as function
approximations , ” Automatica , Vol . 30 , no . 3 , pp . 521 - 525 , 1994 . functions .
For smoother functions , whether this class of fuzzy systems can be designed to
be ...

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Author:

Publisher:

ISBN: STANFORD:36105002083215

Category: Fuzzy systems

Page:

View: 919

Proceedings of 1995 IEEE International Conference on Fuzzy Systems

The International Joint Conference of the Fourth IEEE International Conference
on Fuzzy Systems and the Second International Fuzzy Engineering Symposium :
March 20-24, 1995, Yokohama, Japan. VIII . CONCLUDING REMARKS We have
 ...

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Author:

Publisher:

ISBN: UCSD:31822020810859

Category: Automatic control

Page: 2448

View: 498

Foundations of Fuzzy Systems

Fuzzy Random Variables Part 2 : Algorithms and Examples for the Discrete Case
. Information Sciences , 17 : 253 - 278 , 1978 . M . T . Lamata and S . Moral .
Classification of Fuzzy Measures . Fuzzy Sets and Systems , 33 : 243 - 253 , 1989
.

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Author: Rudolf Kruse

Publisher: Wiley

ISBN: 047194243X

Category: Science

Page: 278

View: 653

A rigorous explanation of fuzzy systems theory plus a detailed illustration of specific practical applications of the powerful engineering tool they represent. Contains a discussion of cutting-edge technology supplemented by the analysis of several successful applications in the areas of approximate reasoning, fuzzy control and fuzzy analysis. Includes scores of exercises, problems, worked examples, step-by-step solutions and comprehensive references.

Electric Power Applications of Fuzzy Systems

APPLICATIONS OF FUZZY SYSTEMS Fuzzy systems have superseded
conventional technologies in many scientific applications and engineering
systems . Fuzzy system techniques are applicable in areas such as control ( the
most widely ...

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Author: M. E. El-Hawary

Publisher: Wiley-IEEE Press

ISBN: UOM:39015043179285

Category: Computers

Page: 343

View: 406

This book offers an introduction to applications of fuzzy system theory to selected areas of electric power engineering. It presents theoretical background material from a practical point of view and then explores a number of applications of fuzzy systems. Most recently, there has been a tremendous surge in research and application articles on this subject. Until now though, there have been no books that put together a practical guide to the fundamentals and applications aspects. Electric Power Applications of Fuzzy Systems presents, under one cover, original contributions by authors who have pioneered in the application of fuzzy system theory to the electric power engineering field. Each chapter contains both an introduction to and a state-of-the-art review of each application area.

Neural Networks and Fuzzy Systems

Since their beginnings fuzzy logic based approaches have consistently gained
ground in many areas including science and engineering . In a world in which
new theories appear only to survive for at most one or two conference seasons ,
this ...

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Author: Shigeo Abe

Publisher: Springer

ISBN: UOM:39015040650627

Category: Computers

Page: 258

View: 324

Neural Networks and Fuzzy Systems: Theory and Applications discusses theories that have proven useful in applying neural networks and fuzzy systems to real world problems. The book includes performance comparison of neural networks and fuzzy systems using data gathered from real systems. Topics covered include the Hopfield network for combinatorial optimization problems, multilayered neural networks for pattern classification and function approximation, fuzzy systems that have the same functions as multilayered networks, and composite systems that have been successfully applied to real world problems. The author also includes representative neural network models such as the Kohonen network and radial basis function network. New fuzzy systems with learning capabilities are also covered. The advantages and disadvantages of neural networks and fuzzy systems are examined. The performance of these two systems in license plate recognition, a water purification plant, blood cell classification, and other real world problems is compared.

Optimization of Fuzzy Systems by Dynamic Switching of Reasoning Methods

[ 61 ] M.A. Lee and H. Takagi , “ Embedding A Priori Knowledge into an
Integrated Fuzzy System Design Method based on Genetic Algorithms , ” Proc . of
the IFSA Congress ( IFSA'93 ) , Seoul , Korea , 1993 , pp.1293-1296 . [ 62 ] M.A.
Lee and ...

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Author: Michael Harvey Smith

Publisher:

ISBN: UCAL:C3385806

Category:

Page: 344

View: 382

Applications and Science of Neural Networks Fuzzy Systems and Evolutionary Computation II

These real - world applications include a fuzzy controller for drilling operation ; a
neural network model to predict the cement bonding quality in oil well completion
; using neural networks and fuzzy logic to rank the importance of input ...

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Author: Society of Photo-optical Instrumentation Engineers

Publisher: Society of Photo Optical

ISBN: 0819432989

Category: Technology & Engineering

Page: 266

View: 846

Proceedings of the Third IEEE Conference on Fuzzy Systems

Fuzzy logic offers a flexible , mathematical representation of uncertainty that can
easily be applied to this problem . 7 depdo correction ( ia ) IV .
IMPLEMENTATION 2 1 0 10 15 23 30 35 20 foco quality A method to determine
depth from defocus ...

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Author:

Publisher:

ISBN: UCSD:31822018838425

Category: Computers

Page: 2118

View: 403

Scientific and Technical Aerospace Reports

Johnson Space Center , North American Fuzzy Logic Processing Society (
NAFIPS 1992 ) , Volume 1 Dec. 1992 p ... INTELLIGENT FUZZY CONTROLLER
FOR EVENT - DRIVEN REAL TIME SYSTEMS c67 Janos Grantner ( Technical ...

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Author:

Publisher:

ISBN: STANFORD:36105009015855

Category: Aeronautics

Page:

View: 783

Fuzzy Systems

Fuzzy Systems: Modeling and Control is part of The Handbooks of Fuzzy Sets Series. The series provides a complete picture of contemporary fuzzy set theory and its applications.

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Author: Hung T. Nguyen

Publisher: Springer Science & Business Media

ISBN: 9781461555056

Category: Mathematics

Page: 519

View: 953

The analysis and control of complex systems have been the main motivation for the emergence of fuzzy set theory since its inception. It is also a major research field where many applications, especially industrial ones, have made fuzzy logic famous. This unique handbook is devoted to an extensive, organized, and up-to-date presentation of fuzzy systems engineering methods. The book includes detailed material and extensive bibliographies, written by leading experts in the field, on topics such as: Use of fuzzy logic in various control systems. Fuzzy rule-based modeling and its universal approximation properties. Learning and tuning techniques for fuzzy models, using neural networks and genetic algorithms. Fuzzy control methods, including issues such as stability analysis and design techniques, as well as the relationship with traditional linear control. Fuzzy sets relation to the study of chaotic systems, and the fuzzy extension of set-valued approaches to systems modeling through the use of differential inclusions. Fuzzy Systems: Modeling and Control is part of The Handbooks of Fuzzy Sets Series. The series provides a complete picture of contemporary fuzzy set theory and its applications. This volume is a key reference for systems engineers and scientists seeking a guide to the vast amount of literature in fuzzy logic modeling and control.