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Advances in Computational Intelligence, Part III

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Cover of 'Advances in Computational Intelligence, Part III'

Table of Contents

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    Book Overview
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    Chapter 1 Fuzzy Arithmetics for Fuzzy n-Poles: When Is Interactivity Irrelevant?
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    Chapter 2 Possibility and Gradual Number Approaches to Ranking Methods for Random Fuzzy Intervals
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    Chapter 3 On Mean Value and Variance of Interval-Valued Fuzzy Numbers
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    Chapter 4 Metric Properties of the Extended Weighted Semi-trapezoidal Approximations of Fuzzy Numbers and Their Applications
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    Chapter 5 Uncertain Evidence in Bayesian Networks: Presentation and Comparison on a Simple Example
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    Chapter 6 Weighted Semi-trapezoidal Approximation of a Fuzzy Number Preserving the Weighted Ambiguity
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    Chapter 7 On the Interval Approximation of Fuzzy Numbers
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    Chapter 8 Approximation of Fuzzy Numbers by F-Transform
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    Chapter 9 Numerical Solution of Linear Fuzzy Fredholm Integral Equations of the Second Kind Using Fuzzy Haar Wavelet
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    Chapter 10 On a View of Zadeh’s Z-Numbers
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    Chapter 11 Solving Real-World Fuzzy Quadratic Programming Problems by a Parametric Method
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    Chapter 12 Naive Bayesian Classifier Based on Neighborhood Probability
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    Chapter 13 Five Weaknesses of ASPIC +
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    Chapter 14 A Feature Reduction Strategy for the Analysis of Voluminous Biomedical Patterns
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    Chapter 15 Discovering the Preferences of Physicians with Regards to Rank-Ordered Medical Documents
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    Chapter 16 Experiences with Eliciting Probabilities from Multiple Experts
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    Chapter 17 Discretisation Effects in Naive Bayesian Networks
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    Chapter 18 Fuzzy Concept Lattices with Incomplete Knowledge
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    Chapter 19 Imperfect Information Fusion Using Rules with Bilattice Based Fixpoint Semantics
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    Chapter 20 Assimilation of Information in RDF-Based Knowledge Base
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    Chapter 21 Quantitative Semantics for Uncertain Knowledge Bases
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    Chapter 22 Weighted Attribute Combinations Based Similarity Measures
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    Chapter 23 Algorithms for Computation of Concept Trilattice of Triadic Fuzzy Context
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    Chapter 24 Classification of Uncertain Data: An Application in Nondestructive Testing
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    Chapter 25 Ant Based Clustering of Two-Class Sets with Well Categorized Objects
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    Chapter 26 Construction Methods for Uninorms via Rotation, Rotation-Annihilation, and Twin Rotation
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    Chapter 27 Natural Means of Indistinguishability Operators
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    Chapter 28 Aggregation Operators for Awareness of General Information
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    Chapter 29 On the Relation between Effort-Dominating and Symmetric Minitive Aggregation Operators
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    Chapter 30 On Migrative t-Conorms and Uninorms
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    Chapter 31 Fuzzy Relations between Two Universes: Soft Assessments of R-neighborhoods
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    Chapter 32 Qualitative Integrals and Desintegrals: How to Handle Positive and Negative Scales in Evaluation
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    Chapter 33 Stability in Aggregation Operators
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    Chapter 34 Negations Generated by Bounded Lattices t-Norms
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    Chapter 35 The Problem of Missing Data in LSP Aggregation
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    Chapter 36 General Interpolation by Polynomial Functions of Distributive Lattices
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    Chapter 37 Aggregation of Weakly Quasi-convex Fuzzy Sets
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    Chapter 38 The Bipolar Universal Integral
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    Chapter 39 Web-Geometric View on Uninorms and Structure of Some Special Classes
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    Chapter 40 Multi-polar Aggregation
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    Chapter 41 An Imprecise Probability Approach to Joint Extensions of Stochastic and Interval Orderings
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    Chapter 42 Imprecise Bernoulli Processes
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    Chapter 43 Possibilistic KNN Regression Using Tolerance Intervals
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    Chapter 44 Classification Based on Possibilistic Likelihood
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    Chapter 45 Maximin and Maximal Solutions for Linear Programming Problems with Possibilistic Uncertainty
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    Chapter 46 Lower Previsions Induced by Filter Maps
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    Chapter 47 Conditioning in Evidence Theory from the Perspective of Multidimensional Models
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    Chapter 48 A New Method for Learning Imprecise Hidden Markov Models
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    Chapter 49 Inference Using Compiled Product-Based Possibilistic Networks
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    Chapter 50 Dynamic Directed Evidential Networks with Conditional Belief Functions: Application to System Reliability
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    Chapter 51 Likelihood-Based Robust Classification with Bayesian Networks
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    Chapter 52 Collecting Information Reported by Imperfect Information Sources
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    Chapter 53 Ranking Aggregation Based on Belief Function
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    Chapter 54 Evaluating the Uncertainty of a Boolean Formula with Belief Functions
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    Chapter 55 Introduction to an Algebra of Belief Functions on Three-Element Frame of Discernment — A Quasi Bayesian Case
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    Chapter 56 Application of Evidence Theory and Discounting Techniques to Aerospace Design
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    Chapter 57 Constructing Rule-Based Models Using the Belief Functions Framework
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    Chapter 58 An Evidential Framework for Associating Sensors to Activities for Activity Recognition in Smart Homes
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    Chapter 59 Positive and Negative Dependence for Evidential Database Enrichment
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    Chapter 60 Handling Interventions with Uncertain Consequences in Belief Causal Networks
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    Chapter 61 K-Modes Clustering Using Possibilistic Membership
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Title
Advances in Computational Intelligence, Part III
Published by
Springer, Berlin, Heidelberg, January 2012
DOI 10.1007/978-3-642-31718-7
ISBNs
978-3-64-231717-0, 978-3-64-231718-7
Editors

Salvatore Greco, Bernadette Bouchon-Meunier, Giulianella Coletti, Mario Fedrizzi, Benedetto Matarazzo, Ronald R. Yager

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 25%
Student > Bachelor 1 13%
Unknown 5 63%
Readers by discipline Count As %
Computer Science 3 38%
Unknown 5 63%