Bücher der Reihe Studies in Fuzziness and Soft Computing

This comprehensive introduction to methods of 'intuitionistic' decision-making explains in detail a variety of models and approaches to interactive decision-making with intuitionistic fuzzy information, as well as systematic coverage of aggregation techniques.

An inclusive primer on intuitionistic fuzzy clustering algorithms, this volume covers priority theory and methods of intuitionistic preference relations. It also shows how fuzzy algorithms can be applied to practicalities such as supply-chain management.

This book explores group decision-making in various scenarios of preference relations, studying the consistency of group decision making using mathematical reasoning, probing decision alternatives using soft computing and optimization and more.

The M logic goes an important step further than the BP logic in that it can distinguish between certain types of information supply sentences which have the same representation in the BP logic as well as in traditional first order logic, although they clearly have different meanings (see example 6.

This comprehensive and accurate survey of state-of-art research on intuitionistic fuzzy sets theory updates the author's work over the past 12 years, and describes the latest general ideas and open problems in this expanding field.

This book provides a number of formulae for implementing the operation extended on fuzzy-valued fuzzy sets, presents basic structures of generalized uncertain fuzzy logic systems, and introduces several of methods to generate fuzzy membership uncertainty.

This book presents a novel approach for exploratory data analysis with ensembles of various neuro-fuzzy systems. It places emphasis on ensembles that can work on incomplete data, thanks to rough set theory.

This book contains an edited collection of eighteen contributions on soft and hard computing techniques and their applications to autonomous robotic systems.

The book focuses on applications of belief functions to business decisions. Three different interpretations (the marginally correct approximation, the qualitative model, and the quantitative model) of belief functions are investigated, and rough set theory and structured query language (SQL) are used to express belief function semantics.

The present book deals with coalition games in which expected pay-offs are only vaguely known. They present detailed views on two main aspects forming the core of game theory: strategic (mostly 2-person) games, and coalitional (or cooperative) games.

The contributions in this book state the complementary rather than competitive relationship between Probability and Fuzzy Set Theory and allow solutions to real life problems with suitable combinations of both theories.

The book focuses on applications of belief functions to business decisions. Three different interpretations (the marginally correct approximation, the qualitative model, and the quantitative model) of belief functions are investigated, and rough set theory and structured query language (SQL) are used to express belief function semantics.

The book aims at surveying results in the application of fuzzy sets and fuzzy logic to economics and engineering. New results include fuzzy non-linear regression, fully fuzzified linear programming, fuzzy multi-period control, fuzzy network analysis, each using an evolutionary algorithm; fuzzy hierarchical analysis using an evolutionary algorithm;

The volume is written in view of explaining to the practitioner the fundamental issues related to computational intelligence paradigms and to offer a fast and friendly-managed introduction to the most recent methods based on computer intelligence in medicine.

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.

This volume provides practicing engineers with new solutions to demanding real-world problems. It presents applications of soft computing to the field of industrial electronicsin two categories, electric power applications and emerging applications.

Colleges give degrees in information science and information management. The purpose of this volume is to introduce key developments and results in the area of generalized information theory, a theory that deals with uncertainty-based information within mathematical frameworks that are broader than classical set theory and probability theory.

Decision makers in managerial and public organizations often encounter de cision problems under conflict or competition, because they select strategies independently or by mutual agreement and therefore their payoffs are then affected by the strategies of the other decision makers.

The primary purpose of this book is to present information about selected topics on the interactions and applications of fuzzy + neural. Fuzzy + neural can mean many things: (1) approximations between fuzzy systems and neu ral nets (Chapter 4); (5) constructing hybrid fuzzy neural nets for certain fuzzy systems (Chapters 9, 10);

The volume provides a comprehensive, up-to-date account on recent developments concerning the incorporation of fuzzy capabilities in Petri Net models. They form an interesting collection of original works that covers a great variety of relevant problems concerning the concept of Fuzzy Petri Net model.

Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation.

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").

Over the last few decades, research on handwriting recognition has made impressive progress. For in stance, High-Tech Solutions in Israel has developed several products for container ID recognition, car license plate recognition and package label recognition.

Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e.

The area known as fuzzy databases covers a bunch of topics among which: -flexible queries addressed to regular databases, -the extension of the notion of a functional dependency, -data mining and fuzzy summarization, -querying databases containing imperfect attribute values represented thanks to possibility distributions.

This ambitious exposition by Malik and Mordeson on the fuzzification of discrete structures not only supplies a solid basic text on this key topic, but also serves as a viable tool for learning basic fuzzy set concepts "from the ground up" due to its unusual lucidity of exposition.

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.

Since human evolution over 2 billion years has seen the co-evolution of social complexity with human language and thought, it is likely that the fuzziness of language and thought is especially intimately formed by the demands of social complexity, just as social complexity is sustained by the inherent fuzziness of language and thought.

"Mathematics of Uncertainty" provides the basic ideas and foundations of uncertainty, covering the fields of mathematics in which uncertainty, variability, imprecision and fuzziness of data are of importance.

The contributions in this book state the complementary rather than competitive relationship between Probability and Fuzzy Set Theory and allow solutions to real life problems with suitable combinations of both theories.