Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Author: Nikola K. Kasabov

Publisher: Marcel Alencar

Published: 1996

Total Pages: 581

ISBN-13: 0262112124

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Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.


Fuzzy Systems

Fuzzy Systems

Author: Hung T. Nguyen

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 532

ISBN-13: 1461555051

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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.


Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems

Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems

Author: V. Bindhu

Publisher: Springer Nature

Published: 2023-03-14

Total Pages: 1048

ISBN-13: 9811977534

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This book includes high-quality research papers presented at the Fourth International Conference on Communication, Computing and Electronics Systems (ICCCES 2022), held at the PPG Institute of Technology, Coimbatore, India, on September 15–16, 2022. The book focuses mainly on the research trends in cloud computing, mobile computing, artificial intelligence and advanced electronics systems. The topics covered are automation, VLSI, embedded systems, optical communication, RF communication, microwave engineering, artificial intelligence, deep learning, pattern recognition, communication networks, Internet of things, cyber-physical systems and healthcare informatics.


Fuzzy Logic Techniques for Autonomous Vehicle Navigation

Fuzzy Logic Techniques for Autonomous Vehicle Navigation

Author: Dimiter Driankov

Publisher: Physica

Published: 2013-03-09

Total Pages: 388

ISBN-13: 3790818356

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In the past decade a critical mass of work that uses fuzzy logic for autonomous vehicle navigation has been reported. Unfortunately, reports of this work are scattered among conference, workshop, and journal publications that belong to different research communities (fuzzy logic, robotics, artificial intelligence, intelligent control) and it is therefore not easily accessible either to the new comer or to the specialist. As a result, researchers in this area may end up reinventing things while being unaware of important existing work. We believe that research and applications based on fuzzy logic in the field of autonomous vehicle navigation have now reached a sufficient level of maturity, and that it should be suitably reported to the largest possible group of interested practitioners, researches, and students. On these grounds, we have endeavored to collect some of the most representative pieces of work in one volume to be used as a reference. Our aim was to provide a volume which is more than "yet another random collection of papers," and gives the reader some added value with respect to the individual papers. In order to achieve this goal we have aimed at: • Selecting contributions which are representative of a wide range of prob lems and solutions and which have been validated on real robots; and • Setting the individual contributions in a clear framework, that identifies the main problems of autonomous robotics for which solutions based on fuzzy logic have been proposed.


Software Engineering with Computational Intelligence

Software Engineering with Computational Intelligence

Author: Jonathan Lee

Publisher: Springer

Published: 2013-11-11

Total Pages: 275

ISBN-13: 3540364234

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It is not an exaggeration to view Professor Lee's book," Software Engineer ing with Computational Intelligence," or SECI for short, as a pioneering contribution to software engineering. Breaking with the tradition of treat ing uncertainty, imprecision, fuzziness and vagueness as issues of peripheral importance, SECI moves them much closer to the center of the stage. It is ob vious, though still not widely accepted, that this is where these issues should be, since the real world is much too complex and much too ill-defined to lend itself to categorical analysis in the Cartesian spirit. As its title suggests, SECI employs the machineries of computational intel ligence (CI) and, more or less equivalently, soft computing (SC), to deal with the foundations and principal issues in software engineering. Basically, CI and SC are consortia of methodologies which collectively provide a body of con cepts and techniques for conception, design, construction and utilization of intelligent systems. The principal constituents of CI and SC are fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing, chaotic computing and machine learning. The leitmotif of CI and SC is that, in general, better performance can be achieved by employing the constituent methodologies of CI and SC in combination rat her than in a stand-alone mode. In what follows, I will take the liberty of focusing my attention on fuzzy logic and fuzzy set theory, and on their roles in software engineering. But first, a couple of points of semantics which are in need of clarification.


Introduction to Fuzzy Logic using MATLAB

Introduction to Fuzzy Logic using MATLAB

Author: S.N. Sivanandam

Publisher: Springer Science & Business Media

Published: 2006-10-28

Total Pages: 442

ISBN-13: 3540357815

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This book provides a broad-ranging, but detailed overview of the basics of Fuzzy Logic. The fundamentals of Fuzzy Logic are discussed in detail, and illustrated with various solved examples. The book also deals with applications of Fuzzy Logic, to help readers more fully understand the concepts involved. Solutions to the problems are programmed using MATLAB 6.0, with simulated results. The MATLAB Fuzzy Logic toolbox is provided for easy reference.


Artificial Intelligence in Control and Decision-making Systems

Artificial Intelligence in Control and Decision-making Systems

Author: Yuriy P. Kondratenko

Publisher: Springer Nature

Published: 2023-04-17

Total Pages: 394

ISBN-13: 3031257596

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This book presents an authoritative collection of contributions reporting on computational intelligence, fuzzy systems as well as artificial intelligence techniques for modeling, optimization, control and decision-making together with applications and case studies in engineering, management and economic sciences. Dedicated to the Academician of the Polish Academy of Sciences, Professor Janusz Kacprzyk in recognition of his pioneering work, the book reports on theories, methods and new challenges in artificial intelligence, thus offering not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike. The book consists of the 18 chapters, presented by distinguished and experienced authors from 16 different countries (Australia, Brazil, Canada, Chile, Germany, Hungary, Israel, Italy, China, R.N.Macedonia, Saudi Arabia, Spain, Turkey, United States, Ukraine, and Vietnam). All chapters are grouped into three parts: Computational Intelligence and Fuzzy Systems, Artificial Intelligence Techniques in Modelling and Optimization, and Computational Intelligence in Control and Decision Support Processes. The book reflects recent developments and new directions in artificial intelligence, including computation method of the interval hull to solutions of interval and fuzzy interval linear systems, fuzzy-Petri-networks in supervisory control of Markov processes in robotic systems, fuzzy approaches for linguistic data summaries, first-approximation analysis for choosing fuzzy or neural systems and type-1 or type-2 fuzzy sets, matrix resolving functions in game dynamic problems, evolving stacking neuro-fuzzy probabilistic networks and their combined learning in online pattern recognition tasks, structural optimization of fuzzy control and decision-making systems, neural and granular fuzzy adaptive modeling, state and action abstraction for search and reinforcement learning algorithms. Among the most successful and perspective implementations in practical areas of human activity are tentative algorithms for neurological disorders, human-centric question-answering system, OWA operators in pensions, evaluation of the perception of public safety through fuzzy and multi-criteria approach, a multicriteria hierarchical approach to investment location choice, intelligent traffic signal control and generative adversarial networks in cybersecurity.


Fuzzy Modeling and Control

Fuzzy Modeling and Control

Author: Andrzej Piegat

Publisher: Physica

Published: 2013-03-19

Total Pages: 737

ISBN-13: 3790818240

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In the last ten years, a true explosion of investigations into fuzzy modeling and its applications in control, diagnostics, decision making, optimization, pattern recognition, robotics, etc. has been observed. The attraction of fuzzy modeling results from its intelligibility and the high effectiveness of the models obtained. Owing to this the modeling can be applied for the solution of problems which could not be solved till now with any known conventional methods. The book provides the reader with an advanced introduction to the problems of fuzzy modeling and to one of its most important applications: fuzzy control. It is based on the latest and most significant knowledge of the subject and can be used not only by control specialists but also by specialists working in any field requiring plant modeling, process modeling, and systems modeling, e.g. economics, business, medicine, agriculture,and meteorology.


Uncertain Rule-Based Fuzzy Systems

Uncertain Rule-Based Fuzzy Systems

Author: Jerry M. Mendel

Publisher: Springer

Published: 2017-05-17

Total Pages: 701

ISBN-13: 3319513702

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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.