Bücher der Reihe Studies in Fuzziness and Soft Computing

Incorporation of a priori knowledge, such as expert knowledge, meta-heuristics and human preferences, as well as domain knowledge acquired during evolu tionary search, into evolutionary algorithms has received increasing interest in the recent years.

This book presents methods of intelligent counting that are human-consistent, are reflections and formalizations of real, human counting procedures. The text is self-contained, systematic and equipped with many examples, figures and tables.

This book presents a new decision theory with imperfect decision-relevant information on environment and a decision maker's behavior. This theory is based on the synthesis of the fuzzy sets theory with perception-based information and the probability theory.

This book introduces readers to fundamental concepts in fuzzy logic.

Text mining is an exciting application ?eld and an area of scienti?c - search that is currently under rapid development. Knowledge Mining draws upon many of the key concepts of knowledge management, data mining and knowledge discovery, meta-analysis and data visualization.

Regarding the scientific com ponent, quite recently the scientific community became familiar with "fuzzy techniques" in image processing, which make use of the framework of fuzzy sets and related theories.

This book deals with expert evaluation models in the form of semantic spaces with completeness and orthogonality properties. The authors describe methods for constructing, analyzing and comparing models, and offer examples drawn from a variety of fields.

This book presents several evolving fuzzy systems approaches using real-world application scenarios to underline the usefulness and necessity of evolving fuzzy systems. The text also outlines potential new applications and raises open problems and new challenges.

This book is focused on mathematical analysis and rigorous design methods for fuzzy control systems based on Takagi-Sugeno fuzzy models, sometimes called Takagi-Sugeno-Kang models.

In our new century, the theory of fuzzy sets and systems is in the core of "Soft Computing" and "Computational Intelligence" and has become a normal scientific theory in the fields of exact sciences and engineering and it is well on its way to becoming normal in the soft sciences as well.

The simplicity and applicability of OWA operators, first introduced in the 1980s, give them intuitive appeal. This volume includes papers on the underlying theory of OWA operators as well as practical applications in vital areas such as environmental modeling.

This compendium brings together leading researchers in the fields of Intelligent Systems and healthcare aiming at medical engineers, healthcare managers and computer scientists worldwide.

The carefully selected contributions report on research, development and real-world experiences of virtual education such as intelligent virtual teaching, web-based adaptive learning systems, intelligent agents or using multiagent intelligence.

This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning.

The book is the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management.

In the late eighties of the twentieth century I encountered a paper referring to mathematics dealing with imprecision applied to medical diagnosis. Lately I have read many papers and books about treating medical tasks solved by using fuzzy ideas.

The papers include reports from the different front of soft computing in various industries and address the problems of different fields of research in fuzzy logic, fuzzy set and soft computing.

This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing (e.g., fuzzy logic, genetic algorithms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and the Semantic Web.

Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems.

This carefully edited book has evolved from presentations made by the participants of a meeting entitled "Fuzzy Logic and the Internet: Enhancing the Power of the Internet", organized by the Berkeley Initiative in Soft Computing (BISC), University of California, Berkeley.

This book is the first ever to deal exclusively with this class of operations. It offers an introduction to Fuzzy Implications, an analytical study of them, and an algebraic exploration into the structures that exist on the set of all FIs.

Fuzzy set approaches are suitable to use when the modeling of human knowledge is necessary and when human evaluations are needed. Fuzzy set theory is now - plied to problems in engineering, business, medical and related health sciences, and the natural sciences.

The papers on rough set theory and its applications placed in this volume present a wide spectrum of problems representative to the present. Therefore many concepts dwelled on in rough set theory are not entirely new, nevertheless the theory can be viewed as an independent discipline on its own rights.

Hybrid intelligent systems combine intelligent computing paradigms including fuzzy logic and bio-inspired optimization algorithms to produce powerful automatic control systems. This volume explains several important control applications of Type-2 fuzzy logic.

The fuzzy logic community is particularly indebted to Abe Mamdani (1941-2010) who, in 1975, in his famous paper An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller, jointly written with his student Sedrak Assilian, introduced the novel idea of fuzzy control.

This book examines fundamental issues of risk assessment in grid computing environments. The authors describe the development of a hybrid probabilistic and possibilistic model for assessing the success of a computing task.

In Part I, the impact of an integro-differential operator on parity logic engines (PLEs) as a tool for scientific modeling from scratch is presented. Part II outlines the fuzzy structural modeling approach for building new linear and nonlinear dynamical causal forecasting systems in terms of fuzzy cognitive maps (FCMs).

With soft computing in humanities and the social sciences at a major turning point, this volume assembles key recent research in a field in which former distinctions between 'hard' science and the humanities are breaking down and opening up fresh horizons.