Uncertain Rule Based Fuzzy Systems
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Author | : Jerry M. Mendel |
Publisher | : Springer |
Total Pages | : 701 |
Release | : 2017-05-17 |
Genre | : Technology & Engineering |
ISBN | : 3319513702 |
Download Uncertain Rule-Based Fuzzy Systems Book in PDF, Epub and Kindle
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.
Author | : Jerry M. Mendel |
Publisher | : Prentice Hall |
Total Pages | : 584 |
Release | : 2001 |
Genre | : Computers |
ISBN | : |
Download Uncertain Rule-based Fuzzy Logic Systems Book in PDF, Epub and Kindle
Jerry Mendel explains the complete development of fuzzy logic systems and explores a new methodology to build better and more intelligent systems. Two case studies are carried throughout the book to illustrate and expand on the theories introduced.
Author | : Jerry M. Mendel |
Publisher | : Springer |
Total Pages | : 0 |
Release | : 2023-09-12 |
Genre | : Technology & Engineering |
ISBN | : 9783031353772 |
Download Explainable Uncertain Rule-Based Fuzzy Systems Book in PDF, Epub and Kindle
The third edition of this textbook presents a further 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 classification to control and to explainable AI (XAI). This latest edition again begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty, leading to type-2 fuzzy sets and systems. New material is included about how to obtain fuzzy set word models that are needed for XAI, similarity of fuzzy sets, a quantitative methodology that lets one explain in a simple way why the different kinds of fuzzy systems have the potential for performance improvements over each other, and new parameterizations of membership functions that have the potential for achieving even greater performance for all kinds of fuzzy systems. For hands-on experience, the book provides information on accessing MATLAB, Java, and Python software to complement the content. The book features a full suite of classroom material.
Author | : Andras - Bardossy |
Publisher | : CRC Press |
Total Pages | : 245 |
Release | : 2022-10-07 |
Genre | : Technology & Engineering |
ISBN | : 0429610866 |
Download Fuzzy Rule-Based Modeling with Applications to Geophysical, Biological, and Engineering Systems Book in PDF, Epub and Kindle
This book presents in a systematic and comprehensive manner the modeling of uncertainty, vagueness, or imprecision, alias "fuzziness," in just about any field of science and engineering. It delivers a usable methodology for modeling in the absence of real-time feedback. The book includes a short introduction to fuzzy logic containing basic definitions of fuzzy set theory and fuzzy rule systems. It describes methods for the assessment of rule systems, systems with discrete response sets, for modeling time series, for exact physical systems, examines verification and redundancy issues, and investigates rule response functions. Definitions and propositions, some of which have not been published elsewhere, are provided; numerous examples as well as references to more elaborate case studies are also given. Fuzzy rule-based modeling has the potential to revolutionize fields such as hydrology because it can handle uncertainty in modeling problems too complex to be approached by a stochastic analysis. There is also excellent potential for handling large-scale systems such as regionalization or highly non-linear problems such as unsaturated groundwater pollution.
Author | : Rómulo Antão |
Publisher | : Springer |
Total Pages | : 136 |
Release | : 2017-07-23 |
Genre | : Technology & Engineering |
ISBN | : 9811046336 |
Download Type-2 Fuzzy Logic Book in PDF, Epub and Kindle
This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.
Author | : Jose Maria Alonso Moral |
Publisher | : Springer |
Total Pages | : 0 |
Release | : 2022-04-08 |
Genre | : Technology & Engineering |
ISBN | : 9783030711009 |
Download Explainable Fuzzy Systems Book in PDF, Epub and Kindle
The importance of Trustworthy and Explainable Artificial Intelligence (XAI) is recognized in academia, industry and society. This book introduces tools for dealing with imprecision and uncertainty in XAI applications where explanations are demanded, mainly in natural language. Design of Explainable Fuzzy Systems (EXFS) is rooted in Interpretable Fuzzy Systems, which are thoroughly covered in the book. The idea of interpretability in fuzzy systems, which is grounded on mathematical constraints and assessment functions, is firstly introduced. Then, design methodologies are described. Finally, the book shows with practical examples how to design EXFS from interpretable fuzzy systems and natural language generation. This approach is supported by open source software. The book is intended for researchers, students and practitioners who wish to explore EXFS from theoretical and practical viewpoints. The breadth of coverage will inspire novel applications and scientific advancements.
Author | : Asli Celikyilmaz |
Publisher | : Springer |
Total Pages | : 443 |
Release | : 2009-04-01 |
Genre | : Computers |
ISBN | : 3540899243 |
Download Modeling Uncertainty with Fuzzy Logic Book in PDF, Epub and Kindle
The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, “The only satisfactory description of uncertainty is probability.
Author | : Jerry M. Mendel |
Publisher | : IEEE |
Total Pages | : 250 |
Release | : 2001-12 |
Genre | : Technology & Engineering |
ISBN | : 9780780348349 |
Download Introduction to Rule-Based Fuzzy Logic Systems Book in PDF, Epub and Kindle
Author | : Nadia Nedjah |
Publisher | : Springer Science & Business Media |
Total Pages | : 252 |
Release | : 2005-05-20 |
Genre | : Computers |
ISBN | : 9783540253228 |
Download Fuzzy Systems Engineering Book in PDF, Epub and Kindle
This book is devoted to reporting innovative and significant progress in fuzzy system engineering. Given the maturation of fuzzy logic, this book is dedicated to exploring the recent breakthroughs in fuzziness and soft computing in favour of intelligent system engineering. This monograph presents novel developments of the fuzzy theory as well as interesting applications of the fuzzy logic exploiting the theory to engineer intelligent systems.
Author | : Witold Pedrycz |
Publisher | : Springer Science & Business Media |
Total Pages | : 399 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461313651 |
Download Fuzzy Modelling Book in PDF, Epub and Kindle
Fuzzy Modelling: Paradigms and Practice provides an up-to-date and authoritative compendium of fuzzy models, identification algorithms and applications. Chapters in this book have been written by the leading scholars and researchers in their respective subject areas. Several of these chapters include both theoretical material and applications. The editor of this volume has organized and edited the chapters into a coherent and uniform framework. The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models. Fuzzy Modelling: Paradigms and Practice provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.