Fuzzy Systems Conference Fuzz 2000

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FUZZ-IEEE 2000

Anonim
FUZZ IEEE 2000 Book PDF

Author : Anonim
Publisher : Unknown
Page : 1080 pages
File Size : 55,8 Mb
Release : 2000
Category : Automatic control
ISBN : OCLC:44496213

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FUZZ-IEEE 2000 by Anonim Pdf

Fuzzy Systems Conference (FUZZ), 2000

IEEE Neural Networks Council
Fuzzy Systems Conference FUZZ 2000 Book PDF

Author : IEEE Neural Networks Council
Publisher : Institute of Electrical & Electronics Engineers(IEEE)
Page : 576 pages
File Size : 48,8 Mb
Release : 2000-05
Category : Automatic control
ISBN : 0780358775

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Fuzzy Systems Conference (FUZZ), 2000 by IEEE Neural Networks Council Pdf

Technologies for Constructing Intelligent Systems 1

Bernadette Bouchon-Meunier,Julio Gutierrez-Rios,Luis Magdalena,Ronald R. Yager
Technologies for Constructing Intelligent Systems 1 Book PDF

Author : Bernadette Bouchon-Meunier,Julio Gutierrez-Rios,Luis Magdalena,Ronald R. Yager
Publisher : Physica
Page : 404 pages
File Size : 42,8 Mb
Release : 2013-03-20
Category : Computers
ISBN : 9783790817973

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Technologies for Constructing Intelligent Systems 1 by Bernadette Bouchon-Meunier,Julio Gutierrez-Rios,Luis Magdalena,Ronald R. Yager Pdf

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.

Genetic Fuzzy Systems

Oscar Cord¢n
Genetic Fuzzy Systems Book PDF

Author : Oscar Cord¢n
Publisher : World Scientific
Page : 492 pages
File Size : 46,8 Mb
Release : 2001
Category : Computers
ISBN : 9810240171

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Genetic Fuzzy Systems by Oscar Cord¢n Pdf

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.

Innovations in Multi-Agent Systems and Application – 1

Dipti Srinivasan
Innovations in Multi Agent Systems and Application 1 Book PDF

Author : Dipti Srinivasan
Publisher : Springer
Page : 302 pages
File Size : 46,5 Mb
Release : 2010-07-17
Category : Technology & Engineering
ISBN : 9783642144356

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Innovations in Multi-Agent Systems and Application – 1 by Dipti Srinivasan Pdf

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.

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Alex A. Freitas
Data Mining and Knowledge Discovery with Evolutionary Algorithms Book PDF

Author : Alex A. Freitas
Publisher : Springer Science & Business Media
Page : 272 pages
File Size : 49,9 Mb
Release : 2013-11-11
Category : Computers
ISBN : 9783662049235

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Data Mining and Knowledge Discovery with Evolutionary Algorithms by Alex A. Freitas Pdf

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

Modern Fuzzy Control Systems and Its Applications

S. Ramakrishnan
Modern Fuzzy Control Systems and Its Applications Book PDF

Author : S. Ramakrishnan
Publisher : BoD – Books on Demand
Page : 468 pages
File Size : 47,7 Mb
Release : 2017-08-30
Category : Mathematics
ISBN : 9789535133896

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Modern Fuzzy Control Systems and Its Applications by S. Ramakrishnan Pdf

Control systems play an important role in engineering. Fuzzy logic is the natural choice for designing control applications and is the most popular and appropriate for the control of home and industrial appliances. Academic and industrial experts are constantly researching and proposing innovative and effective fuzzy control systems. This book is an edited volume and has 21 innovative chapters arranged into five sections covering applications of fuzzy control systems in energy and power systems, navigation systems, imaging, and industrial engineering. Overall, this book provides a rich set of modern fuzzy control systems and their applications and will be a useful resource for the graduate students, researchers, and practicing engineers in the field of electrical engineering.

Fuzzy Rule-Based Inference

Fangyi Li
Fuzzy Rule Based Inference Book PDF

Author : Fangyi Li
Publisher : Springer Nature
Page : 195 pages
File Size : 46,9 Mb
Release : 2024-06-29
Category : Electronic
ISBN : 9789819704910

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Fuzzy Rule-Based Inference by Fangyi Li Pdf

Neuro-Fuzzy Architectures and Hybrid Learning

Danuta Rutkowska
Neuro Fuzzy Architectures and Hybrid Learning Book PDF

Author : Danuta Rutkowska
Publisher : Physica
Page : 292 pages
File Size : 50,9 Mb
Release : 2012-11-13
Category : Computers
ISBN : 9783790818024

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Neuro-Fuzzy Architectures and Hybrid Learning by Danuta Rutkowska Pdf

The advent of the computer age has set in motion a profound shift in our perception of science -its structure, its aims and its evolution. Traditionally, the principal domains of science were, and are, considered to be mathe matics, physics, chemistry, biology, astronomy and related disciplines. But today, and to an increasing extent, scientific progress is being driven by a quest for machine intelligence - for systems which possess a high MIQ (Machine IQ) and can perform a wide variety of physical and mental tasks with minimal human intervention. The role model for intelligent systems is the human mind. The influ ence of the human mind as a role model is clearly visible in the methodolo gies which have emerged, mainly during the past two decades, for the con ception, design and utilization of intelligent systems. At the center of these methodologies are fuzzy logic (FL); neurocomputing (NC); evolutionary computing (EC); probabilistic computing (PC); chaotic computing (CC); and machine learning (ML). Collectively, these methodologies constitute what is called soft computing (SC). In this perspective, soft computing is basically a coalition of methodologies which collectively provide a body of concepts and techniques for automation of reasoning and decision-making in an environment of imprecision, uncertainty and partial truth.

Frontiers of Higher Order Fuzzy Sets

Alireza Sadeghian,Hooman Tahayori
Frontiers of Higher Order Fuzzy Sets Book PDF

Author : Alireza Sadeghian,Hooman Tahayori
Publisher : Springer
Page : 266 pages
File Size : 49,7 Mb
Release : 2014-12-03
Category : Technology & Engineering
ISBN : 9781461434429

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Frontiers of Higher Order Fuzzy Sets by Alireza Sadeghian,Hooman Tahayori Pdf

Frontiers of Higher Order Fuzzy Sets, provides a unified representation theorem for higher order fuzzy sets. The book elaborates on the concept of gradual elements and their integration with the higher order fuzzy sets. This book also is devoted to the introduction of new frameworks based on general T2FSs, IT2FSs, Gradual elements, Shadowed sets and rough sets. Such new frameworks will provide more capable frameworks for real applications. Applications of higher order fuzzy sets in various fields will be discussed. In particular, the properties and characteristics of the new proposed frameworks would be studied. Such frameworks that are the result of the integration of general T2FSs, IT2FSs, gradual elements, shadowed sets and rough sets will be shown to be suitable to be applied in the fields of bioinformatics, business, management, ambient intelligence, medicine, cloud computing and smart grids.

System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models

Salman Zaidi
System Identification of Stochastic Nonlinear Dynamic Systems using Takagi Sugeno Fuzzy Models Book PDF

Author : Salman Zaidi
Publisher : kassel university press GmbH
Page : 155 pages
File Size : 53,7 Mb
Release : 2019-02-22
Category : Fuzzy systems
ISBN : 9783737606509

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System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models by Salman Zaidi Pdf

Some novel approaches to estimate Nonlinear Output Error (NOE) models using TS fuzzy models for a class of nonlinear dynamic systems having variability in their outputs is presented in this dissertation. Instead of using unrealistic assumptions about uncertainty, the most common of which is normality, the proposed methodology tends to capture effects caused by the real uncertainty observed in the data. The methodology requires that the identification method must be repeated offline a number of times under similar conditions. This leads to multiple inputoutput time series from the underlying system. These time series are preprocessed using the techniques of statistics and probability theory to generate the envelopes of response at each time instant. By incorporating interval data in fuzzy modelling and using the theory of symbolic interval-valued data, a TS fuzzy model with interval antecedent and consequent parameters is obtained. The proposed identification algorithm provides for a model for predicting the center-valued response as well as envelopes as the measure of uncertainty in system output.