Integrated Uncertainty in Knowledge Modelling and Decision Making

Name: Integrated Uncertainty in Knowledge Modelling and Decision Making | 4th International Symposium, IUKM 2015, Nha Trang, Vietnam, October 15-17, 2015, Proceedings
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4th International Symposium, IUKM 2015, Nha Trang, Vietnam, October 15-17, 2015, Proceedings

Van-Nam Huynh Masahiro Inuiguchi Thierry Demoeux(Editor)

Springer (Publisher)

Published on 8. October 2015

XIV, 490 pages

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978-3-319-25135-6 (ISBN)

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Content

Intro
Preface
Organization
Epistemic Uncertainty Modeling: The-state-of-the-art
1 Introduction
2 Information Measures
3 Fuzzy Measures
4 Belief Functions
5 Possibility Measures
6 Imprecise Probabilities
7 Conclusions
References
Fuzzy Sets, Multisets, and Rough Approximations
1 Multisets
2 Fuzzy Multisets
3 Rough Approximations
4 Conclusion
References
What Is Fuzzy Natural Logic Abstract
References
Combining Fuzziness and Context Sensitivity in Game Based Models of Vague Quantification
1 Introduction
2 Classifying Vague and Fuzzy Quantifiers
3 Problems with Fuzzy Models of Vague Quantifiers
4 Giles's Game for Lukasiewicz Logic
5 From Type I to Type II Quantifiers Via Precisifications
6 From Type III to Type IV Quantifiers: Random Witnesses
7 Conclusion
References
A New Model of a Fuzzy Associative Memory
1 Introduction
2 Preliminaries
2.1 Implicative Fuzzy Associative Memory
2.2 Algebraic Background
3 Fuzzy Preorders and Their Eigen Sets
3.1 Fuzzy Preorders and their Upper and Lower Sets
3.2 Eigen Sets of Fuzzy Preorders and their ``Skeletons''
4 Fuzzy Preorders and AFIM
5 Illustration
5.1 Experiments with Abstract Images
6 Conclusion
References
Construction of Associative Functions for Several Fuzzy Logics via the Ordinal Sum Theorem
1 Introduction
2 Origin of Ordinal Sum Theorem
3 A Generalization of Ordinal Sums on the Unit Interval [0, 1]
4 Construction of Logical Connectives on [0, 1]
4.1 Properties Required for Fuzzy Logical Connectives
4.2 Realizations of the Properties in the Framework of Ordinal Sum
5 Applications
6 Concluding Remarks
References
Appendix
Cognitively Stable Generalized Nash Equilibrium in Static Games with Unawareness
1 Introduction
2 Model
2.1 Static Games with Unawareness
2.2 Generalized Nash Equilibrium
3 Cognitive Stability
3.1 Problem
3.2 Definition
3.3 Properties
4 Conclusion
References
Maximum Lower Bound Estimation of Fuzzy Priority Weights from a Crisp Comparison Matrix
1 Introduction
2 Lower Bound Based Interval AHP
3 Estimating Fuzzy Weight
4 Numerical Examples
5 Conclusion
References
Logarithmic Conversion Approach to the Estimation of Interval Priority Weights from a Pairwise Comparison Matrix
1 Introduction
2 Interval AHP
3 Logarithmic Conversion Approach
4 Numerical Experiments
4.1 Outline
4.2 Experiments with a Logarithmic Normal Distribution
4.3 Experiments with True Interval Priority Weights
5 Concluding Remarks
References
An Effective Method for Optimality Test Over Possible Reaction Set for Maximin Solution of Bilevel Linear Programming with Ambiguous Lower-Level Objective Function
1 Introduction
2 Problem Formulation
3 Proposed Solution Methods
3.1 K-th Best Method
3.2 Rational Reactions and Possible Optimality Test
3.3 Local Optimality Test
3.4 Global Optimality Test
4 Numerical Experiments
4.1 Problem Generation
4.2 Numerical Results
5 Conclusion
References
Proposal of Grid Area Search with UCB for Discrete Optimization Problem
1 Introduction
2 Fundamental Theory
2.1 Multi-Armed Bandit Problem
2.2 Optimization Problem
2.3 0-1 Knapsack Problem
3 Proposed Method
3.1 Grid Area Search (GAS) for 0-1 Knapsack Problem
3.2 UCB - Grid Area Search
4 Experiment
4.1 Experiment Summary
4.2 Simulation Result
4.3 Discussion
5 Conclusion
References
Why Copulas Have Been Successful in Many Practical Applications: A Theoretical Explanation Based on Computational Efficiency
1 Introduction
2 Why It Is Important to Represent Probability Distributions: Since This Is Necessary For Decision Making
3 Different Computer Representations of Probability Distributions: Analysis from the Viewpointof Decision-Making Applications
4 Formalization of the Problem and the Main Result
5 Conclusions and Future Work
References
A New Measure of Monotone Dependence by Using Sobolev Norms for Copula
1 Introduction
2 Copula and Measures of Dependence
3 A New Measure of Monotone Dependence, (C)
4 Examples
5 Conclusion
References
Why ARMAX-GARCH Linear Models Successfully Describe Complex Nonlinear Phenomena: A Possible Explanation
1 Formulation of the Problem
2 First Approximation: Closed System
3 Second Approximation: Taking External Quantities Into Account
4 Third Approximation: Taking Random Effects into Account
5 Fourth Approximation: Taking Into Account that Standard Deviations Change with Time
6 Conclusions and Future Work
References
A Copula-Based Stochastic Frontier Model for Financial Pricing
1 Introduction
2 Copulas as Dependence Measures
3 Copula-Based Stochastic Frontier Model (SFM)
4 Empirical Results for Model Selection
5 Conclusions
References
Capital Asset Pricing Model with Interval Data
1 Introduction
2 A Review of Real Interval-Valued Data
3 An Interval-Valued Data in a Linear Regression Model
3.1 Goodness of Fit in Linear Regression Model for an Interval-valued Data
4 An Application to the Stock Market
4.1 Capital Asset Pricing Model
4.2 Beta Estimation with Interval Data
4.3 Empirical Results
5 Conclusions and Extension
References
Confidence Intervals for the Difference Between Normal Means with Known Coefficients
1 Introduction
2 Confidence Intervals for the Difference Between Two Normal Population Means
2.1 The Confidence Interval for Based on Pooled Estimate of Variances and Welch-Satterthwaite Methods
2.2 Confidence Intervals for the Difference Between Normal Means with Known Coefficients of Variation
3 Coverage Probabilities and Expected Lengths of Confidence Intervals for with Known Coefficients of Variation
4 Simulation Studies
5 Application
6 Conclusions
References
Approximate Confidence Interval for the Ratio of Normal Means with a Known Coefficient of Variation
Introduction
2 Existing Confidence Interval
3 Proposed Confidence Interval
4 Simulation Study
5 Conclusions
References
Confidence Intervals for the Ratio of Coefficients of Variation of the Gamma Distributions
1 Introduction
2 The Confidence Intervals for the Coefficient of Variation
3 The Confidence Intervals for the Ratio of Coefficients of Variation
3.1 The Confidence Interval for the Ratio of Coefficients of Variation Using the Score Method
3.2 The Confidence Interval for the Ratio of Coefficients of Variation Using the Wald Method
4 Performance of the Confidence Intervals
5 Data Example
6 Conclusions
References
A Deterministic Clustering Framework in MMMs-Induced Fuzzy Co-clustering
1 Introduction
2 FCM Clustering and Deterministic Annealing
3 DA-Based Fuzzy Co-clustering
3.1 FCCM and Its Connection with Statistical Co-clustering Model
3.2 Fuzzy Co-clustering Induced by MMMs and Deterministic Annealing
4 Numerical Experiments
5 Conclusion
References
FCM-Type Co-clustering Transfer Reinforcement Learning for Non-Markov Processes
1 Introduction
2 Fundamental Theory
2.1 Co-clustering
2.2 Q-Learning
2.3 QL-FCCM
3 Proposed Method
4 Transfer Learning Simulation
4.1 Single Pendulum Standing Problem
4.2 Evaluation of Partition Quality of Clustering
5 Simulation Result
6 Conclusion
References
MMMs-Induced Fuzzy Co-clustering with Exclusive Partition Penalty on Selected Items
1 Introduction
2 MMMs-Induced Fuzzy Co-clustering
3 Exclusive Partition of Items in Fuzzy Co-clustering and Sharing Penalties on Selected Items
4 Numerical Experiments
4.1 Document Analysis
4.2 Unsupervised Classification
5 Conclusion
References
Clustering Data and Vague Concepts Using Prototype Theory Interpreted Label Semantics
1 Introduction
2 Label Semantics Framework
3 Distance Measure Based on Logical Expressions
3.1 Prototype Theory Interpretation of Label Semantics
3.2 Distance between Vague Concepts
4 Clustering Mixed Objects
5 Experimental Studies
5.1 Distance Variation
5.2 Clustering Images and Labels
6 Conclusion
References
An Ensemble Learning Approach Based on Rough Set Preserving the Qualities of Approximations
1 Introduction
2 Preliminaries
2.1 Classifications Based on Rough Sets
2.2 Ensemble Learning Approaches
3 An Ensemble Learning Approach Based on Rough Set Preserving the Qualities of Approximations
3.1 The Procedure of the Proposed Method
4 Numerical Experiments
4.1 Results
5 Concluding Remarks
References
Minimum Description Length Principle for Compositional Model Learning
1 Introduction
2 Compositional Models
3 Coding Data
4 Coding Models
5 Model Simplification
6 Conclusions
References
On the Property of SIC Fuzzy Inference Model with Compatibility Functions
1 Introduction
2 Fuzzy Inference Models
2.1 Min--Max--Gravity Model
2.2 Product--Sum--Gravity Model
2.3 Fuzzy Functional Inference Model
2.4 Single Input Connected (SIC) Fuzzy Inference Model
3 Fuzzy Functional SIC Inference Model
4 Additive SIC Inference Models
5 Fuzzy Functional SIC Inference Model with Compatibility Function
6 Conclusion
References
Applying Covering-Based Rough Set Theory to User-Based Collaborative Filtering to Enhance the Quality of Recommendations
1 Introduction
2 Background
2.1 Covering-Based Rough Set
2.2 Reduction Theory of Covering-Based Rough Set
3 Covering-Based Rough Set Model for User-Based Collaborative Filtering
3.1 Purpose
3.2 Model Constructions
3.3 Model Discussion
4 Experiments and Evaluation
4.1 Experimental Setup and Evaluation Metrics
4.2 Comparing CBCF with the Un-reduction Model
4.3 Comparing CBCF with the Classic CF Model
5 Conclusions and Future Work
References
Evidence Combination Focusing on Significant Focal Elements for Recommender Systems
1 Introduction
2 Background and Related Work
2.1 DS Theory
2.2 Related Work
3 Proposed Solution
4 Integrating with Recommender Systems Using Soft Ratings
4.1 Predicting Unrated Data
4.2 Generating Recommendations
5 Implementation and Discussions
6 Conclusions
References
A Multifaceted Approach to Sentence Similarity
1 Introduction
2 Related Work
3 Proposed Method
3.1 Preprocessing
3.2 Word-to-Word Similarity and Information Content
3.3 Word-Sim Measure
3.4 Corpus-Based Information Content
3.5 Word-Based Cosine Similarity
3.6 Word-and-NE-Based Cosine Similarity
3.7 Word Order Similarity
4 Evaluation
5 Conclusion
References
Improving Word Alignment Through Morphological Analysis
1 Introduction
2 Related Work
3 IBM Model 1
3.1 Definition
3.2 Some Problems when Applying to English-Vietnamese Corpora
4 Our Proposal to Extend IBM Model 1
4.1 Motivating Examples
4.2 Our Method
5 Experiments on Word Alignments
5.1 The Word Translation Probabilities
5.2 Improvement in Viterbi Word Alignment
6 Experiments on Translation Performance
7 Conclusion and Future Work
References
Learning Word Alignment Models for Kazakh-English Machine Translation
1 Introduction
2 Learning Word Alignment Models
2.1 Improving Word Alignment
2.2 Morphological Segmentation
3 Evaluation
4 Conclusions
References
Application of Uncertainty Modeling Frameworks to Uncertain Isosurface Extraction
1 Introduction
2 Mathematical Frameworks for Uncertainty Modeling
2.1 Possibility Theory
2.2 Dempster-Shafer Theory
3 Application of Uncertainty Modeling Frameworks to Isosurface Extraction
3.1 Deterministic Marching Cubes Algorithm
3.2 Uncertain Cell Crossing and UMC Template
4 Results and Applications
4.1 Temperature Forecast Example Using Possibility Theory
4.2 Computational Fluid Dynamics Example Using DS Theory
4.3 Synthetic Example Using Probability Theory
5 Summary and Conclusions
References
On Customer Satisfaction of Battery Electric Vehicles Based on Kano Model: A Case Study in Shanghai
1 Introduction
2 The Kano Model
3 Research Methodology
4 Case Study: The BEV in Shanghai
5 Conclusions
References
Co-Movement and Dependency Between New York Stock Exchange, London Stock Exchange, Tokyo Stock Exchange, Oil Price, and Gold Price
1 Introduction
2 Methodology
2.1 Basic Concepts of Copula
2.2 GARCH Models for Univariate Distributions
2.3 C-Vine and D-Vine Copulas
3 Estimation
4 Empirical Results
5 Conclusion
References
Spillovers of Quantitative Easing on Financial Markets of Thailand, Indonesia, and the Philippines
1 Introduction
2 Methods and Procedures
2.1 Markov-Switching Bayesian VAR
2.2 Data, Prior, and Procedures
3 Empirical Results
3.1 Model Fit
3.2 Estimation of MS-BVAR(1) TH group
3.3 Estimation of MS-BVAR(1) IND Group
3.4 Estimation of MS-BVAR(1) PH group
3.5 Regime Probabilities
4 Economic Implication
4.1 Impulse Response
5 Conclusion
A Appendix
References
Impacts of Quantitative Easing Policy of United States of America on Thai Economy by MS-SFABVAR
1 Introduction
2 Methodology
2.1 Bayesian Vector Auto Regressions (BVAR)
2.2 Impulse Response Function
2.3 Markov-Switching Bayesian VAR (MS-BVAR)
3 Empirical Results of Research
3.1 Component Analysis
3.2 VAR Lag Order Selection Criteria Test
3.3 Estimated VAR/BVAR and Its Impulse Response Function
4 Estimated MS-BVAR
5 Conclusion
References
Volatility and Dependence for Systemic Risk Measurement of the International Financial System
1 Introduction
2 Methodology
2.1 The Family GARCH Model
2.2 Multivariate Copulas
2.3 Component Expected Shortfall
3 Empirical Results
3.1 The Data
3.2 Results for Copulas
3.3 Results for Systemic Risk
4 Conclusions
References
Business Cycle of International Tourism Demand in Thailand: A Markov-Switching Bayesian Vector Error Correction Model
1 Introduction
2 Methodology
2.1 Markov Vector Error Correction Model
2.2 Prior Distributions
2.3 Posterior Specifications
3 Empirical Results
3.1 Results of Unit Root Test and Seasonal Unit Root Test
3.2 Lag Length Selection
3.3 Cointegration Test
3.4 Estimates of MS(2)-VECM(1)
3.5 Estimates of MS(2)-BVECM(1)
3.6 Forecasting of International Tourism Demand in Thailand
4 Conclusion
References
Volatility Linkages Between Price Returns of Crude Oil and Crude Palm Oil in the ASEAN Region: A Copula Based GARCH Approach
1 Introduction
2 Methodology
2.1 ARMA-GARCH Model for Marginal Distributions
2.2 Copula Model
3 Data and Empirical Result
3.1 Data
3.2 Results of ARMA-GARCH Model
3.3 Results of Copula Model
4 Application of Copula in VaR and ES Valuation
5 Conclusion and Policy Implication
References
The Economic Evaluation of Volatility Timing on Commodity Futures Using Periodic GARCH-Copula Model
1 Introduction
2 Data
2.1 The Framework of a Minimum Variance Strategy
2.2 Measuring the Performance Gains
3 The Econometric Methods
3.1 Conventional Parametric MGARCH Models
3.2 Copula GARCH Model
4 Candidates for the Margins
4.1 The Period GARCH (P-GARCH) Model
4.2 Conditional Covariance Matrix Estimates
4.3 The Out-of-Sample Comparisons
5 Conclusion
References
On the Estimation of Western Countries' Tourism Demand for Thailand Taking into Account of Possible Structural Changes Leading to a Better Prediction
1 Introduction
2 Literature Reviews
3 Methodology
4 Data
5 Empirical Results
6 Foresting and Discussion
6.1 Forecasting
6.2 Discussion
7 Conclusion
References
Welfare Measurement on Thai Rice Market: A Markov Switching Bayesian Seemingly Unrelated Regression
1 Introducion
2 Welfare Economics
3 Methodology
3.1 Seemingly Unrelated Regression (SUR) Model
3.2 Markov Switching Seemingly Unrelated Regression (MS-SUR)
3.3 Prior and Posterior
3.4 Forecast MSB-SUR
4 Estimation
5 Empirical Results
5.1 Estimation Results for Demand and Supply
5.2 Welfare Measurement
Expected Welfare
5.3 Forecasting Demand and Supply
6 Conclusions
References
Modeling Daily Peak Electricity Demand in Thailand
1 Introduction
2 Standard EVT Approach for Modeling Extremes
3 Dynamic Peak-Over-Threshold Approach
4 Application to Daily Peak Electricity Demand
5 Conclusions
References
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Integrated Uncertainty in Knowledge Modelling and Decision Making

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