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Book Flexible Neuro Fuzzy Systems

Download or read book Flexible Neuro Fuzzy Systems written by Leszek Rutkowski and published by Springer. This book was released on 2013-04-23 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Flexible Neuro-Fuzzy Systems is the first professional literature about the new class of powerful, flexible fuzzy systems. The author incorporates various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data. Flexible Neuro-Fuzzy Systems is the only book that proposes a flexible approach to fuzzy modeling and fills the gap in existing literature. This book introduces new fuzzy systems which outperform previous approaches to system modeling and classification, and has the following features: -Provides a framework for unification, construction and development of neuro-fuzzy systems; -Presents complete algorithms in a systematic and structured fashion, facilitating understanding and implementation, -Covers not only advanced topics but also fundamentals of fuzzy sets, -Includes problems and exercises following each chapter, -Illustrates the results on a wide variety of simulations, -Provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics and civil engineering.

Book Flexible Neuro Fuzzy Systems

Download or read book Flexible Neuro Fuzzy Systems written by Leszek Rutkowski and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Flexible Neuro-Fuzzy Systems is the first professional literature about the new class of powerful, flexible fuzzy systems. The author incorporates various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data. Flexible Neuro-Fuzzy Systems is the only book that proposes a flexible approach to fuzzy modeling and fills the gap in existing literature. This book introduces new fuzzy systems which outperform previous approaches to system modeling and classification, and has the following features: -Provides a framework for unification, construction and development of neuro-fuzzy systems; -Presents complete algorithms in a systematic and structured fashion, facilitating understanding and implementation, -Covers not only advanced topics but also fundamentals of fuzzy sets, -Includes problems and exercises following each chapter, -Illustrates the results on a wide variety of simulations, -Provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics and civil engineering.

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 Fuzzy Neural Intelligent Systems

Download or read book Fuzzy Neural Intelligent Systems written by Hongxing Li and published by CRC Press. This book was released on 2018-10-03 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although fuzzy systems and neural networks are central to the field of soft computing, most research work has focused on the development of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems, especially their mathematical foundations. Fuzzy Neural Intelligent Systems fills this gap. It develops a mathematical basis for fuzzy neural networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing their focus into three main areas of interest, the authors give a systematic, comprehensive treatment of the relevant concepts and modern practical applications: Fundamental concepts and theories for fuzzy systems and neural networks. Foundation for fuzzy neural networks and important related topics Case examples for neuro-fuzzy systems, fuzzy systems, neural network systems, and fuzzy-neural systems Suitable for self-study, as a reference, and ideal as a textbook, Fuzzy Neural Intelligent Systems is accessible to students with a basic background in linear algebra and engineering mathematics. Mastering the material in this textbook will prepare students to better understand, design, and implement fuzzy neural systems, develop new applications, and further advance the field.

Book Neural Fuzzy Systems

Download or read book Neural Fuzzy Systems written by Ching Tai Lin and published by . This book was released on 1996 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Foundations of Neuro Fuzzy Systems

Download or read book Foundations of Neuro Fuzzy Systems written by Detlef Nauck and published by . This book was released on 1997-09-19 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Neuro-Fuzzy Systems reflects the current trend in intelligent systems research towards the integration of neural networks and fuzzy technology. The authors demonstrate how a combination of both techniques enhances the performance of control, decision-making and data analysis systems. Smarter and more applicable structures result from marrying the learning capability of the neural network with the transparency and interpretability of the rule-based fuzzy system. Foundations of Neuro-Fuzzy Systems highlights the advantages of integration making it a valuable resource for graduate students and researchers in control engineering, computer science and applied mathematics. The authors' informed analysis of practical neuro-fuzzy applications will be an asset to industrial practitioners using fuzzy technology and neural networks for control systems, data analysis and optimization tasks.

Book Neuro Fuzzy Control of Industrial Systems with Actuator Nonlinearities

Download or read book Neuro Fuzzy Control of Industrial Systems with Actuator Nonlinearities written by Frank L. Lewis and published by SIAM. This book was released on 2002-01-01 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rigorous stability proofs are further verified by computer simulations, and appendices contain the computer code needed to build intelligent controllers for real-time applications. Neural networks capture the parallel processing and learning capabilities of biological nervous systems, and fuzzy logic captures the decision-making capabilities of human linguistics and cognitive systems.

Book Parallel Processing and Applied Mathematics

Download or read book Parallel Processing and Applied Mathematics written by Roman Wyrzykowski and published by Springer. This book was released on 2004-04-14 with total page 1193 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is our pleasure to provide you with the volume containing the proceedings of the 5th International Conference on Parallel Processing and Applied Mathe- tics, which was held in Cz ̧ estochowa, a Polish city famous for its Jasna Gora Monastery, on September 7–10, 2003. The ?rst PPAM conference was held in 1994 and was organized by the Institute of Mathematics and Computer Science of the Cz ̧ estochowa University of Technology in its hometown. The main idea behind the event was to provide a forum for researchers involved in applied and computational mathematics and parallel computing to exchange ideas in a relaxed atmosphere. Conference organizers hoped that this arrangement would result in cross-pollination and lead to successful research collaborations. In - dition, they hoped that the initially mostly Polish conference would grow into an international event. The fact that these assumptions were correct was proven by the growth of the event. While the ?rst conference consisted of 41 presen- tions, the conference reached 150 participants in Na l ̧ ecz ́ ow in 2001. In this way the PPAM conference has become one of the premiere Polish conferences, and de?nitely the most important one in the area of parallel/distributed computing andappliedmathematics. This year’s meeting gathered almost 200 participants from 32 countries. A strict refereeing process resulted in the acceptance of approximately 150 cont- buted presentations, while the rejection rate was approximately 33%.

Book Artificial Intelligence and Soft Computing

Download or read book Artificial Intelligence and Soft Computing written by Leszek Rutkowski and published by Springer. This book was released on 2016-05-30 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 9692 and LNAI 9693 constitutes the refereed proceedings of the 15th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2016, held in Zakopane, Poland in June 2016. The 134 revised full papers presented were carefully reviewed and selected from 343 submissions. The papers included in the first volume are organized in the following topical sections: neural networks and their applications; fuzzy systems and their applications; evolutionary algorithms and their applications; agent systems, robotics and control; and pattern classification. The second volume is divided in the following parts: bioinformatics, biometrics and medical applications; data mining; artificial intelligence in modeling and simulation; visual information coding meets machine learning; and various problems of artificial intelligence.

Book Advances in Data Analysis with Computational Intelligence Methods

Download or read book Advances in Data Analysis with Computational Intelligence Methods written by Adam E Gawęda and published by Springer. This book was released on 2017-09-21 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a tribute to Professor Jacek Żurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Żurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few. At the same time, the book recognizes and honors Professor Żurada’s dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world’s largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields. The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.

Book Design of Interpretable Fuzzy Systems

Download or read book Design of Interpretable Fuzzy Systems written by Krzysztof Cpałka and published by Springer. This book was released on 2017-01-31 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.

Book Artificial Intelligence and Soft Computing  Part I

Download or read book Artificial Intelligence and Soft Computing Part I written by Leszek Rutkowski and published by Springer. This book was released on 2010-06-20 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the proceedings of the 10th International Conference on Artificial Intelligence and Soft Computing, ICAISC'2010, held in Zakopane, Poland in June 13-17, 2010. The articles are organized in topical sections on Fuzzy Systems and Their Applications; Data Mining, Classification and Forecasting; Image and Speech Analysis; Bioinformatics and Medical Applications (Volume 6113) together with Neural Networks and Their Applications; Evolutionary Algorithms and Their Applications; Agent System, Robotics and Control; Various Problems aof Artificial Intelligence (Volume 6114).

Book Knowledge Based Systems

    Book Details:
  • Author : Rajendra Akerkar
  • Publisher : Jones & Bartlett Learning
  • Release : 2010-08-30
  • ISBN : 0763776475
  • Pages : 375 pages

Download or read book Knowledge Based Systems written by Rajendra Akerkar and published by Jones & Bartlett Learning. This book was released on 2010-08-30 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Based Systems (KBS) are systems that use artificial intelligence techniques in the problem solving process. This text is designed to develop an appreciation of KBS and their architecture and to help users understand a broad variety of knowledge based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 12 chapters are designed to be modular providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material being presented and to stimulate thought and discussion.

Book Intelligent Technologies  theory and Applications

Download or read book Intelligent Technologies theory and Applications written by Peter Sincak and published by IOS Press. This book was released on 2002 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Intelligent Technologies including neural network, evolutionary computations, fuzzy approach and mainly hybrid approaches are very promising tools to build intelligent technologies in general. The progress of each theory or application is provided by a number of various theoretical as well as applicational experiments. Machine intelligence is the only alternative how to increase the level of technology to make technology more human-centred and more effective for society. This book includes theoretical as well as applicational papers in the field of neural networks, fuzzy systems and mainly evolutionary computations which application potential was increased by enormous progress in computer power. Hybrid technologies are still progressing and are trying to make some more applications with their ability to learn and process fuzzy information. Neurogenetic systems are very interesting approach to make systems re-configurable and on-line systems for real-world applications. The book is presenting papers from Japan, USA, Hungary, Poland, Germany, Finland, France, Slovakia, United Kingdom, Czech Republic and some other countries. This publication provides the latest state of the art in the field and could be contributed to theory and applications in the machine intelligence tools and their wide application potential in current and future technologies within the Information Society.

Book Multiple Fuzzy Classification Systems

Download or read book Multiple Fuzzy Classification Systems written by Rafał Scherer and published by Springer. This book was released on 2012-06-26 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy classifiers are important tools in exploratory data analysis, which is a vital set of methods used in various engineering, scientific and business applications. Fuzzy classifiers use fuzzy rules and do not require assumptions common to statistical classification. Rough set theory is useful when data sets are incomplete. It defines a formal approximation of crisp sets by providing the lower and the upper approximation of the original set. Systems based on rough sets have natural ability to work on such data and incomplete vectors do not have to be preprocessed before classification. To achieve better performance than existing machine learning systems, fuzzy classifiers and rough sets can be combined in ensembles. Such ensembles consist of a finite set of learning models, usually weak learners. The present book discusses the three aforementioned fields – fuzzy systems, rough sets and ensemble techniques. As the trained ensemble should represent a single hypothesis, a lot of attention is placed on the possibility to combine fuzzy rules from fuzzy systems being members of classification ensemble. Furthermore, an emphasis is placed on ensembles that can work on incomplete data, thanks to rough set theory. .

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 Rough Sets  Fuzzy Sets  Data Mining and Granular Computing

Download or read book Rough Sets Fuzzy Sets Data Mining and Granular Computing written by Sergei O. Kuznetsov and published by Springer Science & Business Media. This book was released on 2011-06-14 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2011, held in Moscow, Russia in June 2011. The 49 revised full papers presented together with 5 invited and 2 tutorial papers were carefully reviewed and selected from a total of 83 submissions. The papers are organized in topical sections on rough sets and approximations, coverings and granules, fuzzy set models, fuzzy set applications, compound values, feature seletion and reduction, clusters and concepts, rules and trees, image processing, and interactions and visualization.