Information, Uncertainty and Fusion

Author:   Bernadette Bouchon-Meunier ,  Ronald R. Yager ,  Lotfi Zadeh
Publisher:   Springer
Edition:   2000 ed.
Volume:   516
ISBN:  

9780792385905


Pages:   460
Publication Date:   30 September 1999
Format:   Hardback
Availability:   In Print   Availability explained
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Information, Uncertainty and Fusion


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Overview

"The recent IPMU Conference held in La Sorbonne in Paris brought together some of the world's leading experts in uncertainty and information fusion. In this volume, the editors have included a selection of papers from this conference. Underlying much of the processing of information is the need to fuse information; this is especially apparent in attempts to implement ""intelligent"" operations. The development of efficient tools for retrieval of documents, a concern whose importance has increased in proportion to the rapid development of the internet, requires the use of fusion technique. Attempts to construct intelligent agents require the use of sophisticated operations, many of which are of a fusion type, to help model the complex way human beings interact with information and each other. In this volume, the editors have attempted to bring the reader some of the most recent advances in information, uncertainty and fusion."

Full Product Details

Author:   Bernadette Bouchon-Meunier ,  Ronald R. Yager ,  Lotfi Zadeh
Publisher:   Springer
Imprint:   Springer
Edition:   2000 ed.
Volume:   516
Dimensions:   Width: 15.50cm , Height: 2.60cm , Length: 23.50cm
Weight:   1.850kg
ISBN:  

9780792385905


ISBN 10:   079238590
Pages:   460
Publication Date:   30 September 1999
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Information.- Revision by Translation.- Ambiguous Implications in Knowledge-Based Systems Described by Entity-Characteristic Tables.- Functional Dependencies and the Design of Relational Databases Involving Imprecise Data.- A Query Construct for Paraconsistent Databases.- Fuzzy Classifactory Object Recognition for Crisis Detection.- An Approach to Using Degrees of Belief in BDI Agents.- Representation of Comonotonically Additive Functional by Choquet Integral.- On Lower and Upper Approximation of Fuzzy Measures by k-Order Additive Measures.- Generated Fuzzy Quantifiers and Their Orderings.- On Neurofuzzy and Fuzzy Decision Tree Approaches.- A Fuzzy Extension to a Temporal Parsimonious Covering Theory.- Uncertainty.- Probabilities of Future Decisions.- Representations Issues for Risk Scenarios.- Zero Probabilities in Stochastical Independence.- Computing the Probability of Formulas Representing Events in Product Spaces.- Uncertainty Handling for Distributed Database Integration and Knowledge Discovery.- A Rule-Based Language for Probabilistic Reasoning.- Deriving Possibility Distributions from Data Sets Using Confidence Intervals of Probabilities.- Fuzzy Random Variables-Based Modeling with GA-P Algorithms.- A Seasonal Streamflow Forecasting Model Using Neurofuzzy Network.- Allowing Imprecision in Belief Representation Using Fuzzy-Valued Belief Structures.- A Transformational Approach to Fuzzy Propositions.- Four-Valued Logics for Reasoning with Uncertainty in Prioritized Data.- Fusion.- A Mathematical Model for Fuzzy Connectives and its Applicationto Operators Behavioural Study.- Invariance Properties of OWA Operators.- Aggregation Operators as Similarity Relations.- Semantic Meaning of Fuzzy Control Models and Heterogeneous Aggregation Operators.- Maxative Fuzzy Preference Structures.- Directed Possibilistic Graphs and Possibilistic Logic.- A Logic of Supporters.- Building Argumentation Systems on Set Constraint Logic.- Genetic Fuzzy c-Means Algorithm for Automatic Generation of Fuzzy Partitions.- Fast Dempster-Shafer Clustering Using a Neural Network Structure.- Distribution of Contradictive Belief Masses in Combination of Belief Functions.- Relationships Among Ordinal Relations on a Finite Set of Events.

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