Information, Uncertainty and Fusion


Author: Bernadette Bouchon-Meunier,Ronald R. Yager,Lotfi Zadeh

Publisher: Springer Science & Business Media

ISBN: 1461552095

Category: Mathematics

Page: 460

View: 1511

As we stand at the precipice of the twenty first century the ability to capture and transmit copious amounts of information is clearly a defining feature of the human race. In order to increase the value of this vast supply of information we must develop means for effectively processing it. Newly emerging disciplines such as Information Engineering and Soft Computing are being developed in order to provide the tools required. Conferences such as the International Conference on Information Processing and ManagementofUncertainty in Knowledge-based Systems (IPMU) are being held to provide forums in which researchers can discuss the latest developments. The recent IPMU conference held at La Sorbonne in Paris brought together some of the world's leading experts in uncertainty and information fusion. In this volume we have included a selection ofpapers from this conference. What should be clear from looking at this volume is the number of different ways that are available for representing uncertain information. This variety in representational frameworks is a manifestation of the different types of uncertainty that appear in the information available to the users. Perhaps, the representation with the longest history is probability theory. This representation is best at addressing the uncertainty associated with the occurrence of different values for similar variables. This uncertainty is often described as randomness. Rough sets can be seen as a type of uncertainty that can deal effectively with lack of specificity, it is a powerful tool for manipulating granular information.

Uncertainty and Information

Foundations of Generalized Information Theory


Author: George J. Klir

Publisher: John Wiley & Sons

ISBN: 0471755567

Category: Technology & Engineering

Page: 499

View: 8278

Deal with information and uncertainty properly and efficientlyusing tools emerging from generalized information theory Uncertainty and Information: Foundations of Generalized InformationTheory contains comprehensive and up-to-date coverage of resultsthat have emerged from a research program begun by the author inthe early 1990s under the name "generalized information theory"(GIT). This ongoing research program aims to develop a formalmathematical treatment of the interrelated concepts of uncertaintyand information in all their varieties. In GIT, as in classicalinformation theory, uncertainty (predictive, retrodictive,diagnostic, prescriptive, and the like) is viewed as amanifestation of information deficiency, while information isviewed as anything capable of reducing the uncertainty. A broadconceptual framework for GIT is obtained by expanding theformalized language of classical set theory to include moreexpressive formalized languages based on fuzzy sets of varioustypes, and by expanding classical theory of additive measures toinclude more expressive non-additive measures of varioustypes. This landmark book examines each of several theories for dealingwith particular types of uncertainty at the following fourlevels: * Mathematical formalization of the conceived type ofuncertainty * Calculus for manipulating this particular type ofuncertainty * Justifiable ways of measuring the amount of uncertainty in anysituation formalizable in the theory * Methodological aspects of the theory With extensive use of examples and illustrations to clarify complexmaterial and demonstrate practical applications, generoushistorical and bibliographical notes, end-of-chapter exercises totest readers' newfound knowledge, glossaries, and an Instructor'sManual, this is an excellent graduate-level textbook, as well as anoutstanding reference for researchers and practitioners who dealwith the various problems involving uncertainty and information. AnInstructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach


Author: Bilal M. Ayyub,Madan M. Gupta

Publisher: Springer Science & Business Media

ISBN: 146155473X

Category: Computers

Page: 371

View: 7016

Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.

Similarity and Compatibility in Fuzzy Set Theory

Assessment and Applications


Author: Valerie V. Cross,Thomas A. Sudkamp

Publisher: Springer Science & Business Media

ISBN: 9783790814583

Category: Computers

Page: 209

View: 5110

Assessing the degree to which two objects, an object and a query, or two concepts are similar or compatible is a fundamental component of human reasoning and consequently is critical in the development of automated diagnosis, classification, information retrieval and decision systems. The assessment of similarity has played an important role in such diverse disciplines such as taxonomy, psychology, and the social sciences. Each discipline has proposed methods for quantifying similarity judgments suitable for its particular applications. This book presents a unified approach to quantifying similarity and compatibility within the framework of fuzzy set theory and examines the primary importance of these concepts in approximate reasoning. Examples of the application of similarity measures in various areas including expert systems, information retrieval, and intelligent database systems are provided.

Fuzzy Logic

State of the Art


Author: R. Lowen,M.R. Roubens

Publisher: Springer Science & Business Media

ISBN: 9401120145

Category: Mathematics

Page: 587

View: 9278

Fuzzy Logic: State of the Art covers a wide range of both theory and applications of fuzzy sets, ranging from mathematical basics, through artificial intelligence, computer management and systems science to engineering applications. Fuzzy Logic will be of interest to researchers working in fuzzy set theory and its applications.

Fuzzy Information and Engineering

Proceedings of the Second International Conference of Fuzzy Information and Engineering (ICFIE)


Author: Bing-Yuan Cao

Publisher: Springer Science & Business Media

ISBN: 3540714413

Category: Computers

Page: 1032

View: 4300

The Second International Conference on Fuzzy Information and Engineering (ICFIE2007) is a major symposium for scientists, engineers and practitioners in China as well as the world to present their latest results, ideas, developments and applications in all areas of fuzzy information and knowledge engineering. It aims to strengthen relations between industry research laboratories and universities, and to create a primary symposium for world scientists.

Uncertainty-Based Information

Elements of Generalized Information Theory


Author: George Klir,Mark Wierman

Publisher: Springer Science & Business Media

ISBN: 9783790812428

Category: Mathematics

Page: 168

View: 2654

Information is precious. It reduces our uncertainty in making decisions. Knowledge about the outcome of an uncertain event gives the possessor an advantage. It changes the course of lives, nations, and history itself. Information is the food of Maxwell's demon. His power comes from know ing which particles are hot and which particles are cold. His existence was paradoxical to classical physics and only the realization that information too was a source of power led to his taming. Information has recently become a commodity, traded and sold like or ange juice or hog bellies. Colleges give degrees in information science and information management. Technology of the computer age has provided access to information in overwhelming quantity. Information has become something worth studying in its own right. 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. The volume is organized as follows.

Computational Intelligence Systems and Applications

Neuro-Fuzzy and Fuzzy Neural Synergisms


Author: Marian B. Gorzalczany

Publisher: Springer Science & Business Media

ISBN: 9783790814392

Category: Computers

Page: 364

View: 5458

Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge "buried" in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge "encoded" in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed.

Fuzzy Sets Theory and Applications


Author: André Jones,Arnold Kaufmann,Hans-Jürgen Zimmermann

Publisher: Springer Science & Business Media

ISBN: 9789027722621

Category: Mathematics

Page: 403

View: 3328

Problems in decision making and in other areas such as pattern recogni tion, control, structural engineering etc. involve numerous aspects of uncertainty. Additional vagueness is introduced as models become more complex but not necessarily more meaningful by the added details. During the last two decades one has become more and more aware of the fact that not all this uncertainty is of stochastic (random) cha racter and that, therefore, it can not be modelled appropriately by probability theory. This becomes the more obvious the more we want to represent formally human knowledge. As far as uncertain data are concerned, we have neither instru ments nor reasoning at our disposal as well defined and unquestionable as those used in the probability theory. This almost infallible do main is the result of a tremendous work by the whole scientific world. But when measures are dubious, bad or no longer possible and when we really have to make use of the richness of human reasoning in its variety, then the theories dealing with the treatment of uncertainty, some quite new and other ones older, provide the required complement, and fill in the gap left in the field of knowledge representation. Nowadays, various theories are widely used: fuzzy sets, belief function, the convenient associations between probability and fuzzines~ etc ••• We are more and more in need of a wide range of instruments and theories to build models that are more and more adapted to the most complex systems.

Geographical Information Systems for Urban and Regional Planning


Author: Henk J. Scholten,John Stillwell

Publisher: Springer Science & Business Media

ISBN: 9401716773

Category: Social Science

Page: 278

View: 6630

In August 1989, a Summer Institute was held at the Academie van Bouwkunst, the seventeenth century home of Amsterdam's School of Architecture, Town Planning and Landscape. The meeting brought together experts in Geographical Information Systems from throughout the world to address an international audience of planners. The contents of this book reflect many of the themes that were presented and discussed at the conference. The Summer Institute, let alone this volume, would not have been possible without the support of the International Association for the Development and Management of Existing and New Towns (INTNAIVN), the International Society of City and Regional Planners (ISoCaRP), The National Physical Planning Agency of the Netherlands (RPD) and the Berlage Studio. We wish to acknowledge the assistance provided by these organisations and by the various sponsors: The Ministry of Housing, Physical Planning and Environment, the Municipality of Amsterdam, Logisterion b.v., ESRI, UNISYS, MABON b.v., SPSS, PRIME Computer Inc., PANDATA. The provision of hardware facilities by the various computer companies allowed immensely valuable 'hands on' experience to be gained by all the participants.

Fuzzy Hardware

Architectures and Applications


Author: Abraham Kandel,Gideon Langholz

Publisher: Springer Science & Business Media

ISBN: 9780792380290

Category: Computers

Page: 422

View: 1438

Fuzzy hardware developments have been a major force driving the applications of fuzzy set theory and fuzzy logic in both science and engineering. This volume provides the reader with a comprehensive up-to-date look at recent works describing new innovative developments of fuzzy hardware. An important research trend is the design of improved fuzzy hardware. There is an increasing interest in both analog and digital implementations of fuzzy controllers in particular and fuzzy systems in general. Specialized analog and digital VLSI implementations of fuzzy systems, in the form of dedicated architectures, aim at the highest implementation efficiency. This particular efficiency is asserted in terms of processing speed and silicon utilization. Processing speed in particular has caught the attention of developers of fuzzy hardware and researchers in the field. The volume includes detailed material on a variety of fuzzy hardware related topics such as: Historical review of fuzzy hardware research Fuzzy hardware based on encoded trapezoids Pulse stream techniques for fuzzy hardware Hardware realization of fuzzy neural networks Design of analog neuro-fuzzy systems in CMOS digital technologies Fuzzy controller synthesis method Automatic design of digital and analog neuro-fuzzy controllers Electronic implementation of complex controllers Silicon compilation of fuzzy hardware systems Digital fuzzy hardware processing Parallel processor architecture for real-time fuzzy applications Fuzzy cellular systems Fuzzy Hardware: Architectures and Applications is a technical reference book for researchers, engineers and scientists interested in fuzzy systems in general and in building fuzzy systems in particular.

Fuzzy Database Modeling


Author: Adnan Yazici,Roy George

Publisher: Physica

ISBN: 3790818801

Category: Computers

Page: 234

View: 540

Some recent fuzzy database modeling advances for the non-traditional applications are introduced in this book. The focus is on database models for modeling complex information and uncertainty at the conceptual, logical, physical design levels and from integrity constraints defined on the fuzzy relations. The database models addressed here are; the conceptual data models, including the ExIFO and ExIFO2 data models, the logical database models, including the extended NF2 database model, fuzzy object-oriented database model, and the fuzzy deductive object-oriented database model. Integrity constraints are defined on the fuzzy relations are also addressed. A continuing reason for the limited adoption of fuzzy database systems has been performance. There have been few efforts at defining physical structures that accomodate fuzzy information. A new access structure and data organization for fuzzy information is introduced in this book.

Philosophy and Computing

An Introduction


Author: Luciano Floridi

Publisher: Routledge

ISBN: 1134679599

Category: Philosophy

Page: 256

View: 9380

Philosophy and Computing explores each of the following areas of technology: the digital revolution; the computer; the Internet and the Web; CD-ROMs and Mulitmedia; databases, textbases, and hypertexts; Artificial Intelligence; the future of computing. Luciano Floridi shows us how the relationship between philosophy and computing provokes a wide range of philosophical questions: is there a philosophy of information? What can be achieved by a classic computer? How can we define complexity? What are the limits of quantam computers? Is the Internet an intellectual space or a polluted environment? What is the paradox in the Strong Artificial Intlligence program? Philosophy and Computing is essential reading for anyone wishing to fully understand both the development and history of information and communication technology as well as the philosophical issues it ultimately raises.

Fundamentals of Fuzzy Sets


Author: Didier Dubois,Henri M. Prade,Henri Prade

Publisher: Springer Science & Business Media

ISBN: 9780792377320

Category: Business & Economics

Page: 647

View: 2412

Fundamentals of Fuzzy Sets covers the basic elements of fuzzy set theory. Its four-part organization provides easy referencing of recent as well as older results in the field. The first part discusses the historical emergence of fuzzy sets, and delves into fuzzy set connectives, and the representation and measurement of membership functions. The second part covers fuzzy relations, including orderings, similarity, and relational equations. The third part, devoted to uncertainty modelling, introduces possibility theory, contrasting and relating it with probabilities, and reviews information measures of specificity and fuzziness. The last part concerns fuzzy sets on the real line - computation with fuzzy intervals, metric topology of fuzzy numbers, and the calculus of fuzzy-valued functions. Each chapter is written by one or more recognized specialists and offers a tutorial introduction to the topics, together with an extensive bibliography.

Fuzzy Computational Ontologies in Contexts

Formal Models of Knowledge Representation with Membership Degree and Typicality of Objects, and Their Applications


Author: Yi Cai,Ching-man Au Yeung,Ho-fung Leung

Publisher: Springer Science & Business Media

ISBN: 364225456X

Category: Computers

Page: 202

View: 1295

Knowledge Representation plays an essential role in Semantic Web, in particular in automated information processing and communications among software agents. This book, entitled "Fuzzy Computational Ontologies in Contexts: Formal Models of Knowledge Representation with Membership Degree and Typicality, and Their Applications", discusses knowledge representation in Semantic Web. It introduces the relevant background knowledge, models of fuzzy ontologies, importance and priority of properties in concepts, and object typicality in fuzzy ontologies and context-aware ontologies. The book is intended for graduate students, engineers, and researchers in the field of artificial intelligence and computer science. Yi Cai is an Assistant Professor in School of Software Engineering, South China University of Technology, Guangzhou, China. Ching-man Au Yeung is a Senior Engineer in Hong Kong Applied Science and Technology Research Institute, Hong Kong, China. Ho-fung Leung is a Professor and the Chairman of Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings


Author: Eyke Hüllermeier,Rudolf Kruse,Frank Hoffmann

Publisher: Springer Science & Business Media

ISBN: 3642140548

Category: Computers

Page: 764

View: 5913

The International Conference on Information Processing and Management of - certainty in Knowledge-Based Systems, IPMU, is organized every two years with the aim of bringing together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, this conference has been providing a forum for the exchange of ideas between th theoreticians and practitioners working in these areas and related ?elds. The 13 IPMU conference took place in Dortmund, Germany, June 28–July 2, 2010. This volume contains 79 papers selected through a rigorous reviewing process. The contributions re?ect the richness of research on topics within the scope of the conference and represent several important developments, speci?cally focused on theoretical foundations and methods for information processing and management of uncertainty in knowledge-based systems. We were delighted that Melanie Mitchell (Portland State University, USA), Nihkil R. Pal (Indian Statistical Institute), Bernhard Sch ̈ olkopf (Max Planck I- titute for Biological Cybernetics, Tubing ̈ en, Germany) and Wolfgang Wahlster (German Research Center for Arti?cial Intelligence, Saarbruc ̈ ken) accepted our invitations to present keynote lectures. Jim Bezdek received the Kamp ́ede F ́ eriet Award, granted every two years on the occasion of the IPMU conference, in view of his eminent research contributions to the handling of uncertainty in clustering, data analysis and pattern recognition.

An Introduction to Fuzzy Sets

Analysis and Design


Author: Witold Pedrycz,Fernando Gomide

Publisher: MIT Press

ISBN: 9780262161718

Category: Computers

Page: 465

View: 4212

"The Pedrycz and Gomide text is superb in all respects. Its exposition of fuzzy-neural networks and fuzzy-genetic systems adds much to its value as a textbook" -- Lotfi A. Zadeh, University of California, Berkeley. The concept of fuzzy sets is one of the most fundamental and influential tools in computational intelligence. Fuzzy sets can provide solutions to a broad range of problems of control, pattern classification, reasoning, planning, and computer vision. This book bridges the gap that has developed between theory and practice. The authors explain what fuzzy sets are, why they work, when they should be used (and when they shouldn't), and how to design systems using them. The authors take an unusual top-down approach to the design of detailed algorithms. They begin with illustrative examples, explain the fundamental theory and design methodologies, and then present more advanced case studies dealing with practical tasks. While they use mathematics to introduce concepts, they ground them in examples of real-world problems that can be solved through fuzzy set technology. The only mathematics prerequisites are a basic knowledge of introductory calculus and linear algebra.

Uncertainty Data in Interval-Valued Fuzzy Set Theory

Properties, Algorithms and Applications


Author: Barbara Pękala

Publisher: Springer

ISBN: 3319939106

Category: Computers

Page: 181

View: 1446

This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.