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Book Fuzzy Systems Engineering

    Book Details:
  • Author : Nadia Nedjah
  • Publisher : Springer Science & Business Media
  • Release : 2005-05-20
  • ISBN : 9783540253228
  • Pages : 252 pages

Download or read book Fuzzy Systems Engineering written by Nadia Nedjah and published by Springer Science & Business Media. This book was released on 2005-05-20 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Fuzzy Inference System

    Book Details:
  • Author : Mohammad Fazle Azeem
  • Publisher : BoD – Books on Demand
  • Release : 2012-05-09
  • ISBN : 9535105256
  • Pages : 520 pages

Download or read book Fuzzy Inference System written by Mohammad Fazle Azeem and published by BoD – Books on Demand. This book was released on 2012-05-09 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an attempt to accumulate the researches on diverse inter disciplinary field of engineering and management using Fuzzy Inference System (FIS). The book is organized in seven sections with twenty two chapters, covering a wide range of applications. Section I, caters theoretical aspects of FIS in chapter one. Section II, dealing with FIS applications to management related problems and consisting three chapters. Section III, accumulates six chapters to commemorate FIS application to mechanical and industrial engineering problems. Section IV, elaborates FIS application to image processing and cognition problems encompassing four chapters. Section V, describes FIS application to various power system engineering problem in three chapters. Section VI highlights the FIS application to system modeling and control problems and constitutes three chapters. Section VII accommodates two chapters and presents FIS application to civil engineering problem.

Book Computational Intelligence  Soft Computing and Fuzzy Neuro Integration with Applications

Download or read book Computational Intelligence Soft Computing and Fuzzy Neuro Integration with Applications written by Okyay Kaynak and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing is a consortium of computing methodologies that provide a foundation for the conception, design, and deployment of intelligent systems and aims to formalize the human ability to make rational decisions in an environment of uncertainty and imprecision. This book is based on a NATO Advanced Study Institute held in 1996 on soft computing and its applications. The distinguished contributors consider the principal constituents of soft computing, namely fuzzy logic, neurocomputing, genetic computing, and probabilistic reasoning, the relations between them, and their fusion in industrial applications. Two areas emphasized in the book are how to achieve a synergistic combination of the main constituents of soft computing and how the combination can be used to achieve a high Machine Intelligence Quotient.

Book Mathematics of Fuzzy Sets and Fuzzy Logic

Download or read book Mathematics of Fuzzy Sets and Fuzzy Logic written by Barnabas Bede and published by Springer. This book was released on 2012-12-14 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a mathematically-based introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic. Fuzzy Sets have been introduced by Lotfi Zadeh in 1965 and since then, they have been used in many applications. As a consequence, there is a vast literature on the practical applications of fuzzy sets, while theory has a more modest coverage. The main purpose of the present book is to reduce this gap by providing a theoretical introduction into Fuzzy Sets based on Mathematical Analysis and Approximation Theory. Well-known applications, as for example fuzzy control, are also discussed in this book and placed on new ground, a theoretical foundation. Moreover, a few advanced chapters and several new results are included. These comprise, among others, a new systematic and constructive approach for fuzzy inference systems of Mamdani and Takagi-Sugeno types, that investigates their approximation capability by providing new error estimates.

Book Data Mining and Big Data

Download or read book Data Mining and Big Data written by Ying Tan and published by Springer. This book was released on 2017-07-18 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017. The 53 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: association analysis; clustering; prediction; classification; schedule and sequence analysis; big data; data analysis; data mining; text mining; deep learning; high performance computing; knowledge base and its framework; and fuzzy control.

Book Deep Neuro Fuzzy Systems with Python

Download or read book Deep Neuro Fuzzy Systems with Python written by Himanshu Singh and published by Apress. This book was released on 2019-11-30 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current world. This book simplifies the implementation of fuzzy logic and neural network concepts using Python. You’ll start by walking through the basics of fuzzy sets and relations, and how each member of the set has its own membership function values. You’ll also look at different architectures and models that have been developed, and how rules and reasoning have been defined to make the architectures possible. The book then provides a closer look at neural networks and related architectures, focusing on the various issues neural networks may encounter during training, and how different optimization methods can help you resolve them. In the last section of the book you’ll examine the integrations of fuzzy logics and neural networks, the adaptive neuro fuzzy Inference systems, and various approximations related to the same. You’ll review different types of deep neuro fuzzy classifiers, fuzzy neurons, and the adaptive learning capability of the neural networks. The book concludes by reviewing advanced neuro fuzzy models and applications. What You’ll Learn Understand fuzzy logic, membership functions, fuzzy relations, and fuzzy inferenceReview neural networks, back propagation, and optimizationWork with different architectures such as Takagi-Sugeno model, Hybrid model, genetic algorithms, and approximations Apply Python implementations of deep neuro fuzzy system Who This book Is For Data scientists and software engineers with a basic understanding of Machine Learning who want to expand into the hybrid applications of deep learning and fuzzy logic.

Book Advanced Fuzzy Systems Design and Applications

Download or read book Advanced Fuzzy Systems Design and Applications written by Yaochu Jin and published by Physica. This book was released on 2012-12-06 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted.

Book Fuzzy and Neuro Fuzzy Intelligent Systems

Download or read book Fuzzy and Neuro Fuzzy Intelligent Systems written by Ernest Czogala and published by Physica. This book was released on 2012-08-10 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligence systems. We perfonn routine tasks on a daily basis, as for example: • recognition of faces of persons (also faces not seen for many years), • identification of dangerous situations during car driving, • deciding to buy or sell stock, • reading hand-written symbols, • discriminating between vines made from Sauvignon Blanc, Syrah or Merlot grapes, and others. Human experts carry out the following: • diagnosing diseases, • localizing faults in electronic circuits, • optimal moves in chess games. It is possible to design artificial systems to replace or "duplicate" the human expert. There are many possible definitions of intelligence systems. One of them is that: an intelligence system is a system able to make decisions that would be regarded as intelligent ifthey were observed in humans. Intelligence systems adapt themselves using some example situations (inputs of a system) and their correct decisions (system's output). The system after this learning phase can make decisions automatically for future situations. This system can also perfonn tasks difficult or impossible to do for humans, as for example: compression of signals and digital channel equalization.

Book Adaptive Neuro Fuzzy Inference System as a Universal Estimator

Download or read book Adaptive Neuro Fuzzy Inference System as a Universal Estimator written by Constantin Voloşencu and published by BoD – Books on Demand. This book was released on 2024-05-02 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents some recent specialized works of a theoretical study in the domain of adaptive neuro-fuzzy inference systems (ANFIS) for specialists, engineers, professors, and students. It includes five chapters that present new fuzzy systems concepts and promotes them for practical applications, including control of tillage depth, solar radiation prediction, control of power systems, and dynamics of macroeconomic systems. The studies published in the book, through scientific achievements of high-level analysis and design, develop new applications that demonstrate the capabilities of ANFIS. The authors present examples and case studies from their research, providing new solutions and answers to questions related to the emerging concepts and applications of ANFIS.

Book Optimization Using Evolutionary Algorithms and Metaheuristics

Download or read book Optimization Using Evolutionary Algorithms and Metaheuristics written by Kaushik Kumar and published by CRC Press. This book was released on 2019-08-22 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously. This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle. Features: Covers the application of recent and new algorithms Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization Presents the advances of engineering applications for both single-objective and multi-objective optimization problems Offers recent developments from a variety of engineering fields Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering

Book Introduction To Type 2 Fuzzy Logic Control

Download or read book Introduction To Type 2 Fuzzy Logic Control written by Jerry Mendel and published by John Wiley & Sons. This book was released on 2014-06-16 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory book that provides theoretical, practical, and application coverage of the emerging field of type-2 fuzzy logic control Until recently, little was known about type-2 fuzzy controllers due to the lack of basic calculation methods available for type-2 fuzzy sets and logic—and many different aspects of type-2 fuzzy control still needed to be investigated in order to advance this new and powerful technology. This self-contained reference covers everything readers need to know about the growing field. Written with an educational focus in mind, Introduction to Type-2 Fuzzy Logic Control: Theory and Applications uses a coherent structure and uniform mathematical notations to link chapters that are closely related, reflecting the book’s central themes: analysis and design of type-2 fuzzy control systems. The book includes worked examples, experiment and simulation results, and comprehensive reference materials. The book also offers downloadable computer programs from an associated website. 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 learning type-2 fuzzy control theory and its applications Offers experiment and simulation results via downloadable computer programs Features type-2 fuzzy logic background chapters to make the book self-contained Provides an extensive literature survey on both fuzzy logic and related type-2 fuzzy control Introduction to Type-2 Fuzzy Logic Control is an easy-to-read reference book suitable for engineers, researchers, and graduate students who want to gain deep insight into type-2 fuzzy logic control.

Book Fuzzy Inference System

    Book Details:
  • Author : Frank West
  • Publisher :
  • Release : 2015-03-23
  • ISBN : 9781632382108
  • Pages : 0 pages

Download or read book Fuzzy Inference System written by Frank West and published by . This book was released on 2015-03-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book compiles all important researches on the versatile and wide subject of engineering and management using Fuzzy Inference System (FIS). The book talks about the theoretical approaches of FIS, deals with the functions of FIS in management related issues, FIS utilization in varied power system engineering issues and focuses on the FIS application to system making and restraining issues. Lastly, it portrays FIS applications to civil engineering problems.

Book Microelectronic Design of Fuzzy Logic Based Systems

Download or read book Microelectronic Design of Fuzzy Logic Based Systems written by Iluminada Baturone and published by CRC Press. This book was released on 2000-03-30 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy logic has virtually exploded over the landscape of emerging technologies, becoming an integral part of myriad applications and a standard tool for engineers. Until recently, most of the attention and applications have centered on fuzzy systems implemented in software. But these systems are limited. Problems that require real-time operation, low area, or low power consumption demand hardware designed to the fuzzy paradigm - and engineers with the background and skills to design it. Microelectronic Design of Fuzzy Logic-Based Systems offers low-cost answers to issues that software cannot resolve. From the theoretical, architectural, and technological foundation to design tools and applications, it serves as your guide to effective hardware realizations of fuzzy logic. Review fuzzy logic theory and the basic issues of fuzzy sets, operators, and inference mechanisms Explore the trade-offs between efficient theoretical behavior and practical hardware realizations Discover the properties of the possible microelectronic realizations of fuzzy systems - conventional processors, fuzzy coprocessors, and fuzzy chips Investigate the design of fuzzy chips that implement the whole fuzzy inference method into silicon Analyze analog, digital, and mixed-signal techniques Reduce your design effort for fuzzy systems with CAD tools - learn the requirements they should meet and survey current environments. Put it all together - see examples and case studies illustrating how all of this is used to solve particular problems related to control and neuro-fuzzy applications

Book The Parameterization of a Fuzzy Inference System and Its Application to Control

Download or read book The Parameterization of a Fuzzy Inference System and Its Application to Control written by Ping-Wei Chang and published by . This book was released on 1994 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Introduction to Neuro Fuzzy Systems

Download or read book Introduction to Neuro Fuzzy Systems written by Robert Fuller and published by Springer Science & Business Media. This book was released on 2013-06-05 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Genetic Fuzzy Systems  Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases

Download or read book Genetic Fuzzy Systems Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases written by Oscar Cordon and published by World Scientific. This book was released on 2001-07-13 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Fuzzy Systems  Concepts  Methodologies  Tools  and Applications

Download or read book Fuzzy Systems Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2017-02-22 with total page 1795 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.