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Author : Anonim
Publisher : Unknown
Page : 0 pages
File Size : 55,5 Mb
Release : 2000
Category : Automatic control
ISBN : 0780358775
Author : Anonim
Publisher : Unknown
Page : 1080 pages
File Size : 45,6 Mb
Release : 2000
Category : Automatic control
ISBN : OCLC:44496213
Author : IEEE Staff
Publisher : Unknown
Page : 128 pages
File Size : 40,5 Mb
Release : 2012-06-01
Category : Electronic
ISBN : 146730025X
Author : Anonim
Publisher : Unknown
Page : 622 pages
File Size : 42,6 Mb
Release : 2004
Category : Fuzzy sets
ISBN : UOM:39015058327654
Author : Oscar Cord¢n
Publisher : World Scientific
Page : 492 pages
File Size : 49,8 Mb
Release : 2001
Category : Computers
ISBN : 9810240171
In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas. Genetic Fuzzy System represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from a theoretical and a practical perspective. It is a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms.
Author : Zsófia Lendek,T. M. Guerra,Robert Babuška,Bart De Schutter
Publisher : Springer
Page : 196 pages
File Size : 42,9 Mb
Release : 2010-11-26
Category : Technology & Engineering
ISBN : 9783642167768
Many problems in decision making, monitoring, fault detection, and control require the knowledge of state variables and time-varying parameters that are not directly measured by sensors. In such situations, observers, or estimators, can be employed that use the measured input and output signals along with a dynamic model of the system in order to estimate the unknown states or parameters. An essential requirement in designing an observer is to guarantee the convergence of the estimates to the true values or at least to a small neighborhood around the true values. However, for nonlinear, large-scale, or time-varying systems, the design and tuning of an observer is generally complicated and involves large computational costs. This book provides a range of methods and tools to design observers for nonlinear systems represented by a special type of a dynamic nonlinear model -- the Takagi--Sugeno (TS) fuzzy model. The TS model is a convex combination of affine linear models, which facilitates its stability analysis and observer design by using effective algorithms based on Lyapunov functions and linear matrix inequalities. Takagi--Sugeno models are known to be universal approximators and, in addition, a broad class of nonlinear systems can be exactly represented as a TS system. Three particular structures of large-scale TS models are considered: cascaded systems, distributed systems, and systems affected by unknown disturbances. The reader will find in-depth theoretic analysis accompanied by illustrative examples and simulations of real-world systems. Stability analysis of TS fuzzy systems is addressed in detail. The intended audience are graduate students and researchers both from academia and industry. For newcomers to the field, the book provides a concise introduction dynamic TS fuzzy models along with two methods to construct TS models for a given nonlinear system
Author : Miguel Bernal,Antonio Sala,Zsófia Lendek,Thierry Marie Guerra
Publisher : Springer Nature
Page : 349 pages
File Size : 49,6 Mb
Release : 2022-02-05
Category : Technology & Engineering
ISBN : 9783030907730
This book presents a modern perspective on the modelling, analysis, and synthesis ideas behind convex-optimisation-based control of nonlinear systems: it embeds them in models with convex structures. Analysis and Synthesis of Nonlinear Control Systems begins with an introduction to the topic and a discussion of the problems to be solved. It then explores modelling via convex structures, including quasi-linear parameter-varying, Takagi–Sugeno models, and linear fractional transformation structures. The authors cover stability analysis, addressing Lyapunov functions and the stability of polynomial models, as well as the performance and robustness of the models. With detailed examples, simulations, and programming code, this book will be useful to instructors, researchers, and graduate students interested in nonlinear control systems.
Author : IEEE Staff
Publisher : Unknown
Page : 128 pages
File Size : 49,8 Mb
Release : 2009
Category : Electronic
ISBN : 1509069755
Author : Valerie V. Cross,Thomas A. Sudkamp
Publisher : Physica
Page : 207 pages
File Size : 53,6 Mb
Release : 2013-06-05
Category : Mathematics
ISBN : 9783790817935
Assessing the degree to which two objects, an object and a query, or two concepts are similar or compatible is a fundamental component of human reasoning and consequently is critical in the development of automated diagnosis, classification, information retrieval and decision systems. The assessment of similarity has played an important role in such diverse disciplines such as taxonomy, psychology, and the social sciences. Each discipline has proposed methods for quantifying similarity judgments suitable for its particular applications. This book presents a unified approach to quantifying similarity and compatibility within the framework of fuzzy set theory and examines the primary importance of these concepts in approximate reasoning. Examples of the application of similarity measures in various areas including expert systems, information retrieval, and intelligent database systems are provided.
Author : Albert Y. Zomaya
Publisher : Springer Science & Business Media
Page : 758 pages
File Size : 55,8 Mb
Release : 2006-01-10
Category : Computers
ISBN : 0387405321
As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. Neural networks, evolution-based models, quantum computing, and DNA-based computing and simulations are all a necessary part of modern computing analysis and systems development. Vast literature exists on these new paradigms and their implications for a wide array of applications. This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.
Author : Andreas Meier,Edy Portmann,Luis Terán
Publisher : Springer
Page : 207 pages
File Size : 40,9 Mb
Release : 2019-02-28
Category : Business & Economics
ISBN : 9783030033682
This edited book presents the state-of-the-art of applying fuzzy logic to managerial decision-making processes in areas such as fuzzy-based portfolio management, recommender systems, performance assessment and risk analysis, among others. Presenting the latest research, with a strong focus on applications and case studies, it is a valuable resource for researchers, practitioners, project leaders and managers wanting to apply or improve their fuzzy-based skills.
Author : Dan E. Tamir,Naphtali D. Rishe,Abraham Kandel
Publisher : Springer
Page : 684 pages
File Size : 43,5 Mb
Release : 2015-05-23
Category : Technology & Engineering
ISBN : 9783319196831
This book presents a comprehensive report on the evolution of Fuzzy Logic since its formulation in Lotfi Zadeh’s seminal paper on “fuzzy sets,” published in 1965. In addition, it features a stimulating sampling from the broad field of research and development inspired by Zadeh’s paper. The chapters, written by pioneers and prominent scholars in the field, show how fuzzy sets have been successfully applied to artificial intelligence, control theory, inference, and reasoning. The book also reports on theoretical issues; features recent applications of Fuzzy Logic in the fields of neural networks, clustering, data mining and software testing; and highlights an important paradigm shift caused by Fuzzy Logic in the area of uncertainty management. Conceived by the editors as an academic celebration of the fifty years’ anniversary of the 1965 paper, this work is a must-have for students and researchers willing to get an inspiring picture of the potentialities, limitations, achievements and accomplishments of Fuzzy Logic-based systems.
Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 42,7 Mb
Release : 2016
Category : Fuzzy systems
ISBN : 1509006265
Annotation Fuzzy Systems and Applications.
Author : Fangyi Li
Publisher : Springer Nature
Page : 195 pages
File Size : 46,6 Mb
Release : 2024-07-01
Category : Electronic
ISBN : 9789819704910
Author : Dipti Srinivasan
Publisher : Springer
Page : 302 pages
File Size : 42,8 Mb
Release : 2010-07-17
Category : Technology & Engineering
ISBN : 9783642144356
In today’s world, the increasing requirement for emulating the behavior of real-world applications for achieving effective management and control has necessitated the usage of advanced computational techniques. Computational intelligence-based techniques that combine a variety of problem solvers are becoming increasingly pervasive. The ability of these methods to adapt to the dynamically changing environment and learn in an online manner has increased their usefulness in simulating intelligent behaviors as observed in humans. These intelligent systems are able to handle the stochastic and uncertain nature of the real-world problems. Application domains requiring interaction of people or organizations with different, even possibly conflicting goals and proprietary information handling are growing exponentially. To efficiently handle these types of complex interactions, distributed problem solving systems like multiagent systems have become a necessity. The rapid advancements in network communication technologies have provided the platform for successful implementation of such intelligent agent-based problem solvers. An agent can be viewed as a self-contained, concurrently executing thread of control that encapsulates some state and communicates with its environment, and possibly other agents via message passing. Agent-based systems offer advantages when independently developed components must interoperate in a heterogenous environment. Such agent-based systems are increasingly being applied in a wide range of areas including telecommunications, Business process modeling, computer games, distributed system control and robot systems.