Fuzzy Systems Conference Fuzz 2000
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Fuzzy Systems Conference (FUZZ), 2000
Author | : IEEE Neural Networks Council |
Publisher | : Institute of Electrical & Electronics Engineers(IEEE) |
Total Pages | : 576 |
Release | : 2000-05 |
Genre | : Science |
ISBN | : 9780780358775 |
Genetic Fuzzy Systems
Author | : Oscar Cord¢n |
Publisher | : World Scientific |
Total Pages | : 492 |
Release | : 2001 |
Genre | : Computers |
ISBN | : 9789810240172 |
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.
Uncertain Rule-Based Fuzzy Systems
Author | : Jerry M. Mendel |
Publisher | : Springer |
Total Pages | : 701 |
Release | : 2017-05-17 |
Genre | : Technology & Engineering |
ISBN | : 3319513702 |
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.
Technologies for Constructing Intelligent Systems 1
Author | : Bernadette Bouchon-Meunier |
Publisher | : Physica |
Total Pages | : 404 |
Release | : 2013-03-20 |
Genre | : Computers |
ISBN | : 379081797X |
Intelligent systems enhance the capacities made available by the internet and other computer-based technologies. This book deals with the theory behind the solutions to difficult problems in the construction of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of linguistic nature. Various methodologies for these cases are discussed, among which are probabilistic, possibilistic, fuzzy, logical, evidential and network-based frameworks. One purpose of the book is to consider how these methods can be used cooperatively. Topics included in the book include fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, bayesian networks and other network methods, as well as logic-based systems.
Innovations in Multi-Agent Systems and Application – 1
Author | : Dipti Srinivasan |
Publisher | : Springer Science & Business Media |
Total Pages | : 303 |
Release | : 2010-08-10 |
Genre | : Computers |
ISBN | : 3642144349 |
This book provides an overview of multi-agent systems and several applications that have been developed for real-world problems. Multi-agent systems is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexities arising from their interactions. Multi-agent systems allow the subproblems of a constraint satisfaction problem to be subcontracted to different problem solving agents with their own interest and goals. This increases the speed, creates parallelism and reduces the risk of system collapse on a single point of failure. Different multi-agent architectures, that are tailor-made for a specific application are possible. They are able to synergistically combine the various computational intelligent techniques for attaining a superior performance. This gives an opportunity for bringing the advantages of various techniques into a single framework. It also provides the freedom to model the behavior of the system to be as competitive or coordinating, each having its own advantages and disadvantages.
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Author | : Alex A. Freitas |
Publisher | : Springer Science & Business Media |
Total Pages | : 272 |
Release | : 2013-11-11 |
Genre | : Computers |
ISBN | : 3662049236 |
This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
Foundations of Computational Intelligence
Author | : Ajith Abraham |
Publisher | : Springer Science & Business Media |
Total Pages | : 395 |
Release | : 2009-04-21 |
Genre | : Mathematics |
ISBN | : 3642010873 |
Foundations of Computational Intelligence Volume 4: Bio-Inspired Data Mining Theoretical Foundations and Applications Recent advances in the computing and electronics technology, particularly in sensor devices, databases and distributed systems, are leading to an exponential growth in the amount of data stored in databases. It has been estimated that this amount doubles every 20 years. For some applications, this increase is even steeper. Databases storing DNA sequence, for example, are doubling their size every 10 months. This growth is occurring in several applications areas besides bioinformatics, like financial transactions, government data, environmental mo- toring, satellite and medical images, security data and web. As large organizations recognize the high value of data stored in their databases and the importance of their data collection to support decision-making, there is a clear demand for - phisticated Data Mining tools. Data mining tools play a key role in the extraction of useful knowledge from databases. They can be used either to confirm a parti- lar hypothesis or to automatically find patterns. In the second case, which is - lated to this book, the goal may be either to describe the main patterns present in dataset, what is known as descriptive Data Mining or to find patterns able to p- dict behaviour of specific attributes or features, known as predictive Data Mining. While the first goal is associated with tasks like clustering, summarization and association, the second is found in classification and regression problems.
Knowledge-Based Clustering
Author | : Witold Pedrycz |
Publisher | : John Wiley & Sons |
Total Pages | : 336 |
Release | : 2005-05-13 |
Genre | : Technology & Engineering |
ISBN | : 0471708593 |
A comprehensive coverage of emerging and current technology dealing with heterogeneous sources of information, including data, design hints, reinforcement signals from external datasets, and related topics Covers all necessary prerequisites, and if necessary,additional explanations of more advanced topics, to make abstract concepts more tangible Includes illustrative material andwell-known experimentsto offer hands-on experience
Advances in Computational Intelligence
Author | : Hans-Paul Schwefel |
Publisher | : Springer Science & Business Media |
Total Pages | : 327 |
Release | : 2013-03-09 |
Genre | : Computers |
ISBN | : 3662056097 |
The 30 coherently written chapters by leading researchers presented in this anthology are devoted to basic results achieved in computational intelligence since 1997. The book provides complete coverage of the core issues in the field, especially in fuzzy logic and control as well as for evolutionary optimization algorithms including genetic programming, in a comprehensive and systematic way. Theoretical and methodological investigations are complemented by prototypic applications for design and management tasks in electrical engineering, mechanical engineering, and chemical engineering. This book will become a valuable source of reference for researchers active in computational intelligence. Advanced students and professionals interested in learning about and applying advanced techniques of computational intelligence will appreciate the book as a useful guide enhanced by numerous examples and applications in a variety of fields.