Bücher der Reihe Studies in Fuzziness and Soft Computing

It was pointed out nearly 30 years ago by Prewitt (1] that the decisions involved in image segmentation could be postponed by regarding the image parts as fuzzy, rather than crisp, subsets of the image.

This book studies important classes of semirings by using currently documented techniques, by developing new methods for investigating the structure of semirings in a fuzzy context, and extending to the setting of fuzzy semimodules over semirings.

This book presents linguistic fuzzy logic methods applied to social sciences. It presents an approach to the analysis of decision making processes, strategic interactions, causality, and data analysis in social sciences.

Intelligent agents are one of the most promising business tools in our information rich world. An intelligent agent consists of a software system capable of performing intelligent tasks within a dynamic and unpredictable environment.

Being the de-facto standard for data representation and exchange over the Web, XML (Extensible Markup Language) allows the easy development of applications that exchange data over the Web.

We have not witnessed such a large degree of evolution in any other artificial neural network as in the Adaptive Resonance Theory (ART) neural network. Interested readers may refer literature for many more innovations in ART such as Fuzzy ART, ART2, ART2-a, ARTMAP, ARTMAP-PI, ARTMAP-DS, Gaussian ARTMAP, EXACT ART, and ART-EMAP.

Many business decisions are made in the absence of complete information about the decision consequences. The idea is to utilize the potential similarity between the patterns of the past (e.g., "most students used to be profitable") and the patterns of the future (e.g., "students will be profitable").

The landscape of granular computing is immensely rich and involves set theory (interval mathematics), fuzzy sets, rough sets, random sets linked together in a highly synergetic environment.

Applications of Soft Computing have recently increased and methodological development has been strong. It describes the principles and results of industrial applications of Soft Computing methods and introduces new possibilities to gain technical and economic benefits by using this methodology.

This book covers significant recent developments in the field of Intelligent Meth ods applied to eCommerce. The Intelligent Methods considered are mainly Soft Computing Methods that include fuzzy sets, rough sets, neural networks, evolutionary computations, probabilistic and evidential reasoning, multivalued logic, and related fields.

This volume offers the advice of selected expert contributors on the application of heterogeneous methods for managing uncertainty and imprecision in databases. It contains both survey chapters on classic topics such as "flexible querying in databases", and up to date information on "database models to represent imperfect data".

The last two decades have witnessed an enormous growth with regard to ap plications of information theoretic framework in areas of physical, biological, engineering and even social sciences. Claude Shannon in 1948 laid the foundation of the field of information theory in the context of communication theory.

Zadeh, it contains 13 chapters on both theoretical and applied topics in fuzzy set theory, divided in three parts: 1) logics and connectives, 2) data analysis, and 3) media applications. The first part deals with fuzzy logics and with operators on (extensions of) fuzzy sets.

This book sets out the concept of a fuzzy network with rule bases as nodes whose connections are the interactions between the rule bases in the form of outputs fed as inputs. This systematic study will improve the feasibility and transparency of fuzzy models.

Spatial information is pervaded by uncertainty. The concept of uncertainty by itself is understood in a broad sense, including both quantitative and more qualitative approaches, dealing with variability, epistemic uncertainty, as well as with vagueness of terms.

The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.

Furthermore, uncertainty is an attribute of information and, usually, decision-relevant information is uncertain and/or imprecise, therefore the abilities to handle uncertain information and to reason from incomplete knowledge are c- cial features of intelligent behaviour in complex and dynamic environments.

This book examines various aspects of indistinguishability operators. It is intended to be useful to people involved in either theory and applications who are interested in systems dealing with uncertainty and soft computing in general.

The aim of this volume is to show how Fuzzy Sets and Systems can help to provide robust and adaptive heuristic optimization algorithms in a variety of situations. The book presents the state of the art and gives a broad overview on the real practical applications that Fuzzy Sets, based on heuristic algorithms, have.

After 20 years of pursuing rough set theory and its applications a look on its present state and further prospects is badly needed. Furthermore application of rough sets in data mining, in particular, rule induction methods based on rough set theory is presented and discussed.

A simple introduction to relational database systems is given allowing anyone with no background in database theory to appreciate the further contents of this work, especially the extended relational operations and semantics of the ciset relational database model.

The world of text mining is simultaneously a minefield and a gold mine. what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the field of Text Mining -especially in relation to IT- and whether there still remain areas to be covered.

In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Fuzzy random variables have fuzzy distributions. A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance.

Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge.

Summarizing the latest work in the field, this book offers readers a number of approaches to designing stable and efficient FMB control systems, and includes detailed analysis and derivation steps to enable novices to follow the materials effectively.

This book presents an early software reliability prediction model that will help to grow the reliability of software systems by monitoring it in each development phase, from requirement to testing.

With the daily addition of million documents and new users, there is no doubt that the World Wide Web (WWW or Web shortly) is still expanding its global information infrastructure.