Advances in Computational Intelligence, Part III

Name: Advances in Computational Intelligence, Part III | 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, Catania, Italy, July 9 - 13, 2012. Proceedings, Part III
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14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, Catania, Italy, July 9 - 13, 2012. Proceedings, Part III

Salvatore Greco Bernadette Bouchon-Meunier Giulianella Coletti Mario Fedrizzi Benedetto Matarazzo Ronald R. Yager(Herausgeber*in)

Springer (Verlag)

Erschienen am 20. Juli 2012

628 Seiten

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Inhalt

Title
Preface
Organization
Table of Contents - Part III
Fuzzy Numbers and Their Applications
Fuzzy Arithmetics for Fuzzy n-Poles: When Is Interactivity Irrelevant?
Introduction
Preliminaries: -Slices and -Chunks
Results and Examples
References
Possibility and Gradual Number Approaches to Ranking Methods for Random Fuzzy Intervals
Introduction
Preliminaries
Ranking Intervals
Comparison of Random Variables
Comparison of Gradual Numbers
Ranking Fuzzy Intervals
Ranking Ordinal Possibility Distributions
Ranking Fuzzy Intervals as Intervals of Gradual Numbers
Stochastic Dominance of Fuzzy Random Variables
Stochastic Dominance of Fuzzy Random Variables Using Possibilty and Necessity
Stochastic Dominance of Fuzzy Random Variables Using Gradual Random Variables
Statistical Preference between Fuzzy Random Variables
Conclusion
References
On Mean Value and Variance of Interval-Valued Fuzzy Numbers
Introduction
Interval-Valued Fuzzy Numbers
Mean Value for Interval-Valued Fuzzy Numbers
Variance for Interval-Valued Fuzzy Numbers
New Ranking Method for Interval-Valued Fuzzy Numbers
Project Selection with Interval-Valued Fuzzy Numbers
Conclusions
References
Metric Properties of the Extended Weighted Semi-trapezoidal Approximations of Fuzzy Numbers and Their Applications
Introduction
Preliminaries
Extended Weighted Semi-trapezoidal Approximation of a Fuzzy Number
Metric Properties of the Extended Weighted Semi-trapezoidal Approximation
Applications
Weighted Semi-trapezoidal and Semi-triangular Approximations Preserving Parameters
Weighted Semi-trapezoidal, Weighted Semi-triangular Approximations and Aggregation
References
Uncertain Evidence in Bayesian Networks: Presentation and Comparison on a Simple Example
Introduction
Different Types of Evidence in Bayesian Networks
Definitions and Vocabulary
Algorithms Dealing with Uncertain Evidence
Comparison of Different Types of Evidence with a Simple Example
Presentation of the "Snow Example
Junction Tree Algorithm
Hard Evidence
Virtual Evidence
Soft Evidence
Fuzzy Evidence
Fuzzy Reasoning in Bayesian Networks
Conclusion
References
Weighted Semi-trapezoidal Approximation of a Fuzzy Number Preserving the Weighted Ambiguity
Introduction
Preliminaries
Extended Weighted Semi-trapezoidal Approximation and Metric Properties
Weighted Semi-trapezoidal Approximation Preserving the Weighted Ambiguity
Trapezoidal Approximation Preserving Ambiguity
Conclusion
References
On the Interval Approximation of Fuzzy Numbers
Introduction
Fuzzy Numbers
Interval Approximation of a Fuzzy Number
Interval Approximation with Respect to , Distance
Properties
Conclusions
References
Approximation of Fuzzy Numbers by F-Transform
Introduction
F-Transform and Its Basic Properties
F-Transform Approximation of Fuzzy Numbers
Spaces of Functions Generated by F-Transform
Fuzzy Numbers Generated by F-Transform
Fuzzy Arithmetic with F-Transform
F-Transform and Type-2 Fuzzy Numbers
Concluding Remarks
References
Numerical Solution of Linear Fuzzy Fredholm Integral Equations of the Second Kind Using Fuzzy Haar Wavelet
Introduction
Preliminaries
Proposed Method for Solving Linear FFIE-2
Error Estimation
Numerical Examples
Conclusions
References
On a View of Zadeh's Z-Numbers
Introduction
Modeling Z-Valuations
Operations on Z-Valuations
Reasoning with Z-Valuations
Linguistic Summaries and Z-Valuations
References
Solving Real-World Fuzzy Quadratic Programming Problems by a Parametric Method
Introduction
Using a Parametric Approach to Solve Quadratic Programming Problems with Fuzzy Constraints
Numerical Experiments
Portfolio Selection Problem
Economic Dispatch Problem
Conclusions
References
Information Processing and Management of Uncertainty in Knowledge-Based Systems
Naive Bayesian Classifier Based on Neighborhood Probability
Introduction
The Related Works
The Normal Method
The Kernel Method
NBC Based on Neighborhood Probability-NPNBC
The Basic Idea of NPNBC
The Principle of NPNBC
The Feasibility of NPNBC
Experiments and Results
Conclusion
References
FiveWeaknesses of ASPIC+
Introduction
APIC+ Argumentation Framework
Tarski's Monotonic Logics
Rules as Object Level Language
Rules as Reasoning Patterns
Conclusion
References
A Feature Reduction Strategy for the Analysis of Voluminous Biomedical Patterns
Introduction
Dimensionality Reduction Using Feature Sampling
Feature Performance Histogram
Aggregating Feature Regions
Experiment Design
Validation Protocol
Experiment Parameters
Results and Discussion
Conclusion
References
Discovering the Preferences of Physicians with Regards to Rank-Ordered Medical Documents
Introduction
Background Research
Experimental Design
Results
Discussion
References
Experiences with Eliciting Probabilities from Multiple Experts
Introduction
The Context
Set-Up of the Project Meetings
Taking a Quantitative Perspective: Summary Statistics
The Data Obtained, the Analyses and the Results
Discussion
Taking a Qualitative Perspective: Stochastic Dominance
The Data Obtained, the Analyses and the Results
Discussion
Conclusions
References
Discretisation Effects in Naive Bayesian Networks
Introduction
Preliminaries
Naive Bayesian Networks
Sensitivity Analysis
Studying the Effects of Discretisation
Binary Discretisation in Two-Class Naive Bayesian Networks
Discretisation in Naive Bayesian Networks in General
Conclusions and Further Research
References
Fuzzy Concept Lattices with Incomplete Knowledge
Introduction
Preliminaries
Residuated Lattices and Fuzzy Sets
Formal Concept Analysis in Fuzzy Setting
Residuated Lattices with Variables
Incomplete Contexts and Their Concept Lattices
Illustrative Example
Conclusion
References
Imperfect Information Fusion Using Rules with Bilattice Based Fixpoint Semantics
Introduction
Extended Logic Programs on Bilattices
Bilattice Based Fixpoint Semantics
Computational Results
Further Results and Ongoing Work
References
Assimilation of Information in RDF-Based Knowledge Base
Introduction
Repository of User's Experience and Knowledge
Personal Linked Data and Special Properties
Personal Linked Data as User's Knowledge Base
Information Assimilation Mechanism
Relevance Determination
Knowledge Integration
Case Study
Experimental Setup
Integration Process
Conclusion
References
Quantitative Semantics for Uncertain Knowledge Bases
Introduction
The Logic Lm
Logic Programs and Their Quantitative Semantics
Programs
Valuations and Models
Quantitative Semantics of Positive Programs
Quantitative Semantics of Programs with Negation
Knowledge Bases with Uncertain Information
Quantitative Semantics for Knowledge Bases
Knowledge Base Updating
Properties of Updates
Conclusion
References
Weighted Attribute Combinations Based Similarity Measures
Introduction
Preliminaries
Weighted Attribute Combinations Based Similarities
Learning the Significance Assessment
Experimental Results
Conclusions and Future Works
References
Algorithms for Computation of Concept Trilattice of Triadic Fuzzy Context
Introduction
Preliminaries
Fuzzy Logic and Fuzzy Sets
Formal Concept Analysis, Triadic Concept Analysis
Reduction to the Ordinary Case
Trias in Fuzzy Setting
Conclusions
References
Classification of Uncertain Data: An Application in Nondestructive Testing
Motivation and Background
State of the Art
Classification of MFL Data
Classification under Uncertainty
Modeling Uncertainties with Trust Management
Concept and Realization
Investigation and Results
Investigation Set-Up
Pure Classification Performance
Assessment of the Results with Trust Management
Discussion
Conclusion and Outlook
References
Ant Based Clustering of Two-Class Sets with Well Categorized Objects
Preliminaries
Algorithm
Experiments
Conclusions
References
Aggregation Functions
Construction Methods for Uninorms via Rotation, Rotation-Annihilation, and Twin Rotation
Introduction and Preliminaries
Preliminaries
Rotation of Uninorms
Rotation-Annihilation with Uninorms
Twin Rotation of Semigroups
References
Natural Means of Indistinguishability Operators
Introduction
Preliminaries
The Lattices of Indistinguishability Operators, Sets of Extensional Fuzzy Subsets, Upper and Lower Approximations
Natural Means Operating on Indistinguishability Operators, Sets of Extensional Fuzzy Subsets, Upper and Lower Approximations
Concluding Remarks
References
Aggregation Operators for Awareness of General Information
Introduction
Preliminaries
Statment of the Problem: Awareness AWJ
Some Aggregation Operators for AWJ
Solution of the Problem
Conclusion
References
On the Relation between Effort-Dominating and Symmetric Minitive Aggregation Operators
Preliminaries
Notational Convention
Aggregation Operators
Effort-Dominating Impact Functions
Symmetric Minitive Aggregation Operators
The Relationship between the Two Classes
Conclusions
References
On Migrative t-Conorms and Uninorms
Introduction
Preliminaries
Uninorms
(,S0)-Migrative t-Conorms
(,U0)-Migrative Uninorms
When U0 is in Umin
When U0 is in Umax
Conclusions and Future Work
References
Fuzzy Relations between Two Universes: Soft Assessments of R-neighborhoods
Introduction
Assessments by Pairs of Fuzzy Sets
Interval-Valued Assessments
Assessments by Pairs of Fuzzy Relations
Conclusion
References
Qualitative Integrals and Desintegrals: How to Handle Positive and Negative Scales in Evaluation
Introduction
General Setting and Motivation
Algebraic Framework
Aggregation and Scale Polarity
Three Qualitative Weighted Aggregations for Positive Scales
Three Qualitative Weighting Methods for Negative Scales
Properties of the Drastic Desintegrals
Concluding Remarks
References
Stability in Aggregation Operators
Introduction
Stability of a Family of Aggregation Operators
Weak Stability of a Family of Aggregation Operators
Stability Levels of Some Well-Known Families of Aggregation Operators
Conclusions and Final Remarks
References
Negations Generated by Bounded Lattices t-Norms
Introduction
Bounded Lattices
Negations on L
T-norms on L
Negation on L Obtained from t-norms on L
Final Remarks
References
The Problem of Missing Data in LSP Aggregation
Introduction
The Structure of LSP Criterion Functions
Penalty-Controlled Numerical Coding of Missing Data
Missingness-Tolerant Aggregation
Conclusions
References
General Interpolation by Polynomial Functions of Distributive Lattices
Introduction and Motivation
Preliminaries
Main Results
Further Work
Applications and Concluding Remarks
References
Aggregation of Weakly Quasi-convex Fuzzy Sets
Introduction
Case of Quasi-convex Fuzzy Sets
Main Results
Conclusion
References
The Bipolar Universal Integral
Introduction
Basic Concepts
The Universal Integral and the Bipolar Universal Integral
An Illustrative Example
The Bipolar Universal Integral with Respect to a Level Dependent Bi-capacity
Conclusions
References
Web-Geometric View on Uninorms and Structure of Some Special Classes
Introduction
Preliminaries
Web-Geometric View on Uninorms
Structure of Uninorms Given by Idempotent and Involutive t-Norms and t-Conorms
Concluding Remarks
References
Multi-polar Aggregation
Introduction
m-Polar Aggregation Operators
Properties of Multi-polar Aggregation Operators
Metric on K[0,1]
Properties of m-Polar Aggregation Operators
Conclusions
References
Imprecise Probabilities
An Imprecise Probability Approach to Joint Extensions of Stochastic and Interval Orderings
Introduction and Motivation
Comparing Random Variables v.s. Ill-Known Quantities
Stochastic Orderings
A Common Formulation
Comparing Ill-Known Quantities Modeled by Real Intervals
Preference Relations within Imprecise Probability Theory
Generalizations of First Stochastic Dominance
Generalizations of Expectation Dominance
Generalizations of Statistical Preference
A General Common Expression of Preference between Gambles
General Formulation
The Special Case of Fuzzy Intervals
References
Imprecise Bernoulli Processes
Introduction
Desirability and Coherence
Imprecise Bernoulli Experiments
Exchangeability
Imprecise Bernoulli Processes
Justifying a Sensitivity Analysis Approach
Conclusions
References
Possibilistic KNN Regression Using Tolerance Intervals
Introduction
Possibility Theory
Inferring Possibility Distribution from Data
Interval Prediction with K-Nearest Neighbors
K-Nearest Neighbors (KNN)
Possibilistic KNN with Fixed K
KNN Interval Regression with Variable K Using 0.95 CTP Distribution
Application to Aircraft Trajectory Prediction
Conclusion
References
Classification Based on Possibilistic Likelihood
Introduction
Background
Possibility Distribution
A Possibility Distribution as a Family of Probability Distributions
Possibilistic Likelihood
A Possibilistic Likelihood-Based Classifier
Principle
Construction and Learning of a Possibilistic Classifier
Experimentations
Conclusions and Further Works
References
Maximin and Maximal Solutions for Linear Programming Problems with Possibilistic Uncertainty
Introduction
Reformulation as a Decision Problem
Probability Mass Functions
Generalizing the Probabilistic Case
Intervals
Possibility Distributions
Conclusions
References
Lower Previsions Induced by Filter Maps
Introduction and Motivation
Basic Notions
Motivation
Induced Lower Previsions
Properties of Induced Lower Previsions
Conclusion
References
Probabilistic Graphical Models with Imprecision: Theory and Applications
Conditioning in Evidence Theory from the Perspective of Multidimensional Models
Introduction
Basic Concepts
Set Projections and Extensions
Set Functions
Conditioning
Conditioning of Events
Conditional Variables
Conditional Independence and Irrelevance
Independence
Irrelevance
Relationship between Independence and Irrelevance
Conclusions
References
A New Method for Learning Imprecise Hidden Markov Models
Introduction
Hidden Markov Models and Basic Notions
Precise Hidden Markov Models
Imprecise Hidden Markov Models
Learning Imprecise Local Uncertainty Models
Imprecise Dirichlet Model
Known State Sequence
Unknown State Sequence
Imprecision of the Imprecise Local Uncertainty Models
The Baum-Welch Algorithm
Likelihood in Hidden Markov Models
Expectation Step
Maximisation Step
Predicting the Earth's Earthquake Rate
Introduction
Results
6 Conclusion
References
Inference Using Compiled Product-Based Possibilistic Networks
Introduction
Basic Backgrounds
Possibility Theory
Possibilistic Networks
Compilation Concepts
Compilation-Based Inference of G*
Encoding and Compilation Phase
Inference Phase
Prod-DNNF vs Min-DNNF
Conclusion
References
Dynamic Directed Evidential Networks with Conditional Belief Functions: Application to System Reliability
Introduction
Static and Dynamic Directed Graphical Models
Static Directed Graphical Models
Dynamic Directed Graphical Models
Static and Dynamic Directed Evidential Networks with Conditional Belief Functions
Directed Evidential Networks with Conditional Belief Functions
Dynamic Directed Evidential Networks with Conditional Belief Functions (DDEVN)
Propagation in DDEVN
Illustrative Case Study
Application of the DDEVN to the Valve System Reliability
DEN and DDEVN for the System Reliability Assessment
Conclusion
References
Likelihood-Based Robust Classification with Bayesian Networks
Introduction
Background
Classification with Bayesian Networks
Likelihood-Based Learning of Imprecise-Probabilistic Models
Robust Likelihood-Based Classifiers
A Demonstrative Example
Coping with Zero Counts
Analytic Formulae for the Upper Envelope of the Likelihood
Preliminary Results
Conclusions and Outlooks
References
Belief Function Theory: Basics and/or Applications
Collecting Information Reported by Imperfect Information Sources
Introduction
A Logical Model
The Logical Framework
Agent i Is in Direct Contact with the Source
There Is a Third Agent between Agent i and the Source
Taking Uncertainty into Account
The Numerical Model
Agent i Is in Direct Contact with the Source
There Is a Third Agent between i and the Source
Concluding Remarks
References
Ranking Aggregation Based on Belief Function
Introduction
Ranking Aggregation Methods
Belief Functions Theory
Method
Notation and Definition of the Problem
Belief Ranking Estimator
Experimental Results on Synthetic Data
Conclusion
Evaluating the Uncertainty of a Boolean Formula with Belief Functions
Introduction
Evaluation of the Probability of a Boolean Expression
Without Any Independence Hypothesis
When Variables xi Are Stochastically Independent
The Case of Independent Sources of Information
The Belief and Plausibility of a Boolean Formula
Conjunctions and Disjunctions of Literals
Application to Fault-Trees
General Case
Comparison between Interval Analysis and Dempster-Shafer Theory
Conclusion
References
Introduction to an Algebra of Belief Functions on Three-Element Frame of Discernment - A Quasi Bayesian Case
Introduction
Preliminaries
General Primer on Belief Functions
Belief Functions on 2-Element Frame of Discernment
Dempster's Semigroup
BFs on n-Element Frames of Discernment
Dempster's Semigroup of Belief Functions on 3-Element Frame of Discernment 3
Basics
The Extended Dempster's Semigroup
Subalgebras of Dempster's Semigroup
Subalgebras of D0 and Ideas of Subalgebras of D3
The Subgroups/Subalgebras of Bayesian Belief Functions
The Subsemigroup of Quasi-bayesian Belief Functions
Ideas for Future Research and Open Problems
Conclusion
References
Application of Evidence Theory and Discounting Techniques to Aerospace Design
Introduction
Theory of Belief Functions
Evidential Operations
Case Study
Implementation of Scenario
Conclusion
References
Constructing Rule-Based Models Using the Belief Functions Framework
Introduction
Belief Functions
Basic Concepts
Evidential c-Means Algorithm
Rule-Based Model
Regression Problem
Model Structure
Model Parameters
Examples
Conclusions and Future Work
References
An Evidential Framework for Associating Sensors to Activities for Activity Recognition in Smart Homes
Introduction
Activities and Uncertainty in Smart Homes
Basics of the Dempster-Shafer (DS) Theory of Evidence
Formulation of Association between Sensors and Activities
Uncertainty with Sensor Sources
A Preliminary Evaluation
Summary and Future Work
References
Positive and Negative Dependence for Evidential Database Enrichment
Introduction
Theory of Belief Functions
Conditioning
Generalized Bayesian Theorem and Disjunctive Rule of Combination
Evidential Database
Independence
Clustering
Independence Measure
Negative and Positive Dependence
Example
Conclusion
References
Handling Interventions with Uncertain Consequences in Belief Causal Networks
Introduction
Belief Function Theory and Causal Networks
Basics of Belief Function Theory
Belief Function Causal Networks
Jeffrey Rule of Conditioning
Jeffrey's Rule in a Probabilistic Framework
Extension of Jeffrey's Rule to the Belief Function Framework
Observations vs Interventions
Observations
Interventions
Graphical Representation of Interventions
Belief Graph Mutilation for Interventions Controlling the State of the Variable
Belief Graph Augmentation for Interventions Interacting with Initial Causes
Conclusion
References
K-Modes Clustering Using Possibilistic Membership
Introduction
The K-Modes Method
Possibility Theory
Possibility Distribution
Possibilistic Clustering
The K-Modes Method with Possibilistic Membership
Experiments
The Framework
Evaluation Criteria
Experimental Results
Conclusion
References
Author Index

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