Preface
Organization
Contents
EUSFLAT General Track
The Inevitability of Vagueness in Fuzzy Logic
1 J v Heijenoort: the Inevitability of Vagueness
2 M. Black: the ineluctability of vagueness
2.1 Defining Vagueness
2.2 What Exactly Is Vagueness?
2.3 Vagueness and Human Intelligence
3 C.G. Hempel and Vagueness
References
A Fuzzy Cognitive Map Learning Approach for Coronary Artery Disease Diagnosis in Nuclear Medicine
1 Introduction
2 Material and Methods
2.1 CAD Dataset
2.2 Methodology of the Proposed Framework DeepFCM
3 Results
4 Discussion
5 Conclusions
References
Discussing Uninorms on Bounded Lattices Using Closure and Interior Operators
1 Introduction
2 Preliminaries
3 Construction Approaches for Uninorms
4 Conclusion
References
Norms and Discrete Choquet Integrals Induced by Submodular Fuzzy Measures: A Discussion
1 Introduction
2 Background and Related Works
2.1 Norms and Distances
2.2 Fuzzy Measures and Discrete Choquet Integrals
2.3 Related Works
3 A Discussion on MIFM and Induced Choquet Integrals
3.1 Reminder: MIFM Induced Choquet Integrals
3.2 Discussing the Relations Between MIFM and Norms
3.3 Discussing the Relations Between MIFM and Submodularity
4 Discrete Choquet Integrals and Norms: A Discussion
4.1 Characterization of the Discrete Case
4.2 Case of Possibility Measure Induced Choquet Integral
4.3 General Case
5 Conclusion
References
Some Existence Results for Fuzzy Differential Equations with a Metric-Basic Derivative of Type (ii)
1 Introduction
2 Preliminaries
3 Existence of a Solution in [0,tN]
References
Elements of Relational Power Set Theories for Semiring-Valued Fuzzy Structures
1 Introduction
2 Preliminaries
3 Relational Power Set Theories in Kleisli Categories SetR and SetR
4 Relational Power Set Theorie in Categories Set(R) and Set(R)
5 Example
6 Conclusions
References
Partial Fuzzy Relational Equations and the Dragonfly Operations – What Happens If...?
1 Introduction and Preliminaries
1.1 Introduction
1.2 System of Fuzzy Relational Equations
2 Dragonfly Operations and Properties
2.1 Dragonfly Algebra
2.2 Auxiliary Properties
3 System with the Direct Product
3.1 Solvability Issues
3.2 Beyond the Solvability – Approximate Solutions
4 Conclusion
References
Conceptuality Degree of Oriented Crisply Generated Fuzzy Preconcepts
1 Introduction
2 Preliminaries
3 Fuzzy Preconcepts and Fuzzy Preconcept Lattices
4 Operators R : LXLY, R : LY LX and Crisply Generated -Preconcept Join Semilattice
4.1 Operators R : LXLY and R : LY LX
4.2 Crisply Generated -Preconcept Join Semilattice
4.3 Degree of Conceptuality of -Preconcepts
4.4 Operators D1ob, D2ob, D3ob,D4ob : P0 L
5 Examples
5.1 Examples Related to Zoology
5.2 Example of the Assessment of Solar Activity
6 Conclusion
References
IFS-IBA Logical Aggregation with Frank t-norms
1 Introduction
2 IFS-IBA Approach
2.1 Intuitionistic Fuzzy Sets
2.2 Interpolative Boolean Algebra
2.3 Essentials of IFS-IBA
3 Correlation of IFS
4 Parametric t-norms
4.1 Frank t-norm
5 IFS-IBA Logical Aggregation
6 Application to Gifted Student Ranking
7 Conclusion
References
Fuzzy Equivalence Relations for Solving a Multiple Objective Linear Programming Problem
1 Introduction
2 Preliminaries
2.1 Triangular Norms
2.2 Fuzzy Equivalence Relations
3 Zimmermann Approach for MOLP Problem
4 Fuzzy Equivalence Relations Approach
5 Conclusion
References
Applied Large-Scale Group Decision Making Using Systemic Consensus and Fuzzy Method of Comparative Linguistic Expressions
1 Introduction
2 Preliminary Definitions
2.1 Literature Review
2.2 Group Decision-Making Methods
2.3 Fuzzy Decision-Making
3 Framework of an Integrative Fuzzy Decision-Making Process (I-FDM)
3.1 I-FDM Framework of the Decision-Making Process
3.2 Comparative Linguistic Expressions (CLEs)
3.3 Two-Dimensional Fuzzy Logic Table
3.4 The Ranking of the Alternatives
4 Case Study
4.1 Methodology
4.2 Data Processing of CLE Membership-Values
4.3 Application of the Two-Dimensional Fuzzy Logic Table
4.4 Evaluation
5 Conclusion
References
Machine Learning and Fuzzy Measures: A Real Approach to Individual Classification
1 Introduction
2 Preliminaries
3 Mathematical Model
3.1 On the Calculation of the Predictive Fuzzy Measure
3.2 On the Calculation of the Estimation y'
4 An Application and Interpretation of the Method
4.1 Definition of the Problem
4.2 Comparison of 3 with Other Methods
5 Conclusions and Further Research
References
Exploring the Automatic Selection of Aggregation Methods in Group Recommendation
1 Introduction
2 Preliminaries
2.1 Group Recommender Systems
2.2 Automatic Algorithm Selection in Recommender Systems
3 A General Framework for Automatic Selection of the Aggregation Measure
4 Automatic Selection of the Aggregation Function in Content-Based Group Recommendation
5 Experiments
5.1 Experimental Protocol
5.2 Results
6 Conclusions
References
Splitting Rules for Monotone Fuzzy Decision Trees
1 Introduction
2 Fuzzy Rank Discrimination Measures
3 Enforcing Monotonicity in Decision Tree Construction
4 Conclusion
References
Root Cause Analysis with Fuzzy Cognitive Maps and Correlation Coefficient
1 Introduction
2 Main Aspects of Fuzzy Cognitive Maps
3 Methodology
3.1 Dataset Acquisition
3.2 Processing
3.3 Pearson Correlation and Fuzzy Cognitive Maps
4 Results and Discussion
5 Summary
References
A Multi-criteria Group Decision-Making Method in Changeable Scenarios Based on Self-adjustment of Weights Using Reciprocal Preference Relations
1 Introduction
2 Preliminaries
3 MCGDM Method in Changeable Scenarios Based on Self-adjustment of Weight
3.1 Debate and Provide the Preferences
3.2 Verification of the Consensus by Analysis
3.3 Computation of the Weights of the Criteria
3.4 Aggregation of Criteria
3.5 Obtaining the Ranking of Alternatives
4 Illustrative Example
5 Discussion
6 Conclusions
References
Towards Imprecise Scores in Multi-criteria Decision Making with Ranked Weights
1 Introduction
2 Preliminaries
2.1 Approximate Weighting Methods
3 Towards Imprecise Scores
3.1 Imprecise Scores as Intervals
3.2 Imprecise Scores as Triangular Fuzzy Numbers
4 An Illustrative Example
4.1 Scores as Intervals
4.2 Scores as Fuzzy Numbers
5 Discussion and Conclusion
References
A Multitask Deep Learning Approach for Staples and Wound Segmentation in Abdominal Post-surgical Images
1 Introduction
2 Methodology
2.1 Dataset
2.2 Metrics
2.3 Neural Network
2.4 Adaptive Balancing Tasks: GradNorm
3 Experimental Setting
3.1 Training Details
4 Results and Discussion
5 Conclusions and Future Work
References
FIDOC: A New Combination of Fuzzy Impulse Noise Detection and Open-Close Filtering
1 Introduction
2 A Brief Review of the Adaptive Image Filter Based on the Fuzzy Transform (ATIF)
2.1 The Noise Detection Stage
2.2 The Filtering Stage
3 The Filtering Stage of the I-FMMOCS
4 Reduction of General Impulsive Noise Using a New Combination of Noise Detection and Impulse Noise Filtering
5 Experimental Results
6 Concluding Remarks
References
Fuzzy Fingerprinting Large Pre-trained Models
1 Introduction
2 Background and Related Work
2.1 Pre-trained Models
2.2 Fuzzy Fingerprints
3 Fuzzy Fingerprinting Large Pre-trained Models
3.1 Fine-Tuning BERT and RoBERTa
3.2 Fuzzy Fingerprint Creation from Pre-trained Models
3.3 Classification Using Fuzzy Fingerprints
4 Experiments
4.1 Datasets
4.2 Experimental Details
4.3 Results and Discussion
5 Conclusions and Future Work
References
AGOP General Track
Aggregation Using Penalty and Moderate Deviation Functions
1 Introduction
2 Preliminaries
2.1 Moderate Deviation Function
2.2 Local Penalty Function
2.3 Faithful Local Penalty Function
2.4 Weighted Penalty Function
3 Moderate Deviation-Based and Penalty-Based Aggregations
3.1 Mean as a Penalty and Deviation-Based Function
3.2 Median and Other Quantiles
4 Generalization of the Global Moderate Deviation Function and Penalty Function
5 Conclusion
References
An Interval-Valued Multi-attribute Decision Making Based on Combined QUALIFLEX-EAST Methodology
1 Introduction
2 Preliminaries
2.1 Interval-Valued Fuzzy Set
3 Interval Valued Multiplicative Preference Relation
3.1 Saaty's Definition of Consistency for Multiplicative Preference Relation and Its Extension with Interval Data
3.2 Transformation Between Utility Value and Multiplicative Preference Relation
4 The New Ranking Mechanism Combining QUALIFLEX and EAST
4.1 Construction of Pairwise Comparison Matrix for Each Attribute Based on the Decision Matrix
4.2 Construction of the Aggregated Matrix After Accumulation of the Preference Matrix over All Attributes
4.3 Enumerating only Possible Preference Orders from Aggregated Preference Matrix Using Graph Theoretic Approach
4.4 Computation of Concordance/Discordance Index for Every Possible Preference Ordering
5 Conclusion
References
On an Edge Detector Based on Ordinal Sums of Conjunctive and Disjunctive Aggregation Functions
1 Introduction
2 Preliminaries
3 From the Edge Detector Based on Uninorms to a New One Based on Ordinal Sums
3.1 Edge Detection Using Uninorms
3.2 Towards Edge Detection Using Commutative Aggregation Functions
4 Experimental Setup
4.1 Image Dataset
4.2 Evaluation Metrics
4.3 Parameter Tuning
5 Analysis of the Results
6 Conclusions and Future Work
References
SPECIAL SESSION 1: Interval Uncertainty
Why Fractional Fuzzy
1 Formulation of the Problem
2 Fuzzy Control Techniques: A Brief Reminder
3 Fractional Fuzzy Techniques: Motivations, Description, Successes, and Remaining Challenge
4 Our Main Idea and How it Explains the Empirical Success of Fractional Fuzzy Techniques
5 Fractional Fuzzy Techniques are Optimal – In Some Reasonable Sense
6 Conclusions
References
Interval-Valued and Set-Valued Extensions of Discrete Fuzzy Logics, Belnap Logic, and Color Optical Computing
1 Formulation of the Problem
2 Why Interval-Valued and Set-Valued Extensions of Discrete Fuzzy Logics
3 Interval-Valued and Set-Valued Extensions of 2-Valued Logic
4 Interval-Valued and Set-Valued Extensions of 3-Valued Logic and Their Relation to Color Optical Computing
5 Conclusions
References
SPECIAL SESSION 2: Information Fusion Techniques Based on Aggregation Functions, Preaggregation Functions and Their Generalizations
Measuring the Distance Between Machine Learning Models Using F-Space
1 Introduction
2 Fuzzy Measures
3 Probabilistic Metric Space
4 Metrics for Machine Learning Models
4.1 Case 1: Additive Measure
4.2 Case 2: Fuzzy Measures
4.3 The Interpretation of the Fuzzy Measures
5 Conclusions
References
On the Relationship Between Multidistances and n-Distances Revisited
1 Introduction
2 Preliminaries
3 From Multidistances to n-Distances
4 From n-Distances to Multidistances
5 Conclusions
References
Fuzzy Integrals for Edge Detection
1 Introduction
2 Preliminaries
2.1 Fuzzy Measure, Choquet and Sugeno Integral
2.2 Evaluation of the Proposal
3 Methodology
3.1 Dataset
3.2 Experimental Framework
4 Obtained Results
5 Conclusions and Future Works
References
Transformation Techniques for Interval-Valued Intuitionistic Fuzzy Sets: Applications to Aggregation and Decision Making
1 Introduction
2 Preliminary Concepts
2.1 Intuitionistic Fuzzy Sets: Concepts and operations
2.2 Interval-Valued Intuitionistic Fuzzy Sets: Concepts and Results
3 Results
3.1 Scores and Accuracies
3.2 Aggregation
3.3 Multi-attribute Decision Making Using Representation Theorems
4 Concluding Remarks
References
SPECIAL SESSION 3: Evaluative Linguistic Expressions, Generalized Quantifiers and Applications
Verifying Validity of Selected Forms of Syllogisms with Intermediate Quantifiers Using Peterson's Rules
1 Introduction
2 Preliminaries
2.1 The Algebraic Structure of the Truth Values
2.2 Evaluative Linguistic Expressions
2.3 The Theory of Intermediate Quantifiers
3 Extended Syllogisms with Intermediate Quantifiers
4 Extended Peterson's Rules for Checking Validity of Syllogisms
5 Checking Validity of Syllogisms by Extended Peterson's Rules
5.1 Valid Syllogisms Satisfy Extended Peterson's Rules
5.2 Syllogisms Which Satisfy Extended Peterson's Rules are Valid
6 Example of Peterson's Logical Syllogism
7 Conclusion
References
From Graded Aristotle's Hexagon to Graded Peterson's Hexagon of Opposition in Fuzzy Natural Logic
1 Introduction
2 Preliminaries
2.1 Formal Definition of fuzzy Intermediate Quantifiers
2.2 Theories of Evaluative Linguistic Expressions
2.3 Fuzzy Intermediate Quantifiers
3 From Graded Aristotle's Square to Graded Aristotle's Hexagon
3.1 Generalized Definition that Form Graded Structures
3.2 Formal Proofs of Properties with A,E,I,O
3.3 Formal Proofs of Properties of A,E,Y
3.4 Formal Proofs of Properties of U,O,I
3.5 Formal Proofs of Properties of Y,U
3.6 Formal Proofs of Properties of A,E,I,O,U,Y
4 Future Direction: From Graded Peterson's Square to Graded Peterson's Hexagon
4.1 Selected Properties of Fuzzy Intermediate Quantifiers
5 Conclusion
References
Analysis of the Number of Valid Peterson's Syllogisms
1 Introduction
2 Preliminaries
2.1 The Algebraic Structure
2.2 Evaluative Linguistic Expressions
2.3 Mathematical Definition of Fuzzy Intermediate Quantifiers
2.4 Formalization of Syllogisms
3 The Number of Strongly Valid Peterson's Syllogisms
3.1 The Importance of the Size of the Quantifier
3.2 Discussion about Non-trivial Syllogisms of Figure-III
3.3 Peterson's Formula for Concrete Figure
3.4 Assumptions
3.5 Figure-I
3.6 Figure-II
3.7 Figure-III
3.8 Figure IV
4 Conclusion and Future Work
References
Logical Relations Between T-Scaling Quantifiers and Their Implications in Fuzzy Relational Concept Analysis
1 Introduction
2 Preliminaries
2.1 Mathematical Tools for Fuzzy Logic
2.2 Fuzzy Formal Concept Analysis
2.3 Fuzzy Relational Concept Analysis
2.4 Extracting Concepts from a Fuzzy Relational Context Family
3 Relations of Opposition Between Fuzzy Formal Contexts
4 Relations Between FFCA Operators
5 Conclusions and Future Directions
References
An Analysis of FRCA Quantifiers
1 Introduction
2 Fuzzy Relational Concept Analysis
2.1 Fuzzy Formal Concept Analysis
2.2 Fuzzy Relational Concept Analysis
2.3 Extracting Concepts from a Fuzzy Relational Context Family
3 Comparing Fuzzy Scaling and t-Scaling Quantifiers
4 Future Directions
References
SPECIAL SESSION 4: Neural Networks under Uncertainty and Imperfect Information
Arbitrariness of Outward Closeness in Laplacian Dimensionality Reduction
1 Introduction
2 Laplacian Dimensionality Reduction
3 Laplacian Decomposition
4 Inverse Problem
4.1 Arbitrariness of Outward Closeness
5 Conclusions
References
SPECIAL SESSION 5: Imprecision Modeling and Management in XAI Systems
Fuzzy Logic Function as a Post-hoc Explanator of the Nonlinear Classifier
1 Introduction
2 Background
2.1 Feature Importance Measures
2.2 Post-hoc Fuzzy Explanator
3 Results
4 Conclusions
References
A Bayesian Interpretation of Fuzzy C-Means
1 Introduction
2 Fuzzy C-Means
3 Bayesian Interpretation
4 Conclusive Remarks and Hints for Further Investigation
References
The Role of Speculations for Explainable and Trustworthy Artificial Intelligence: A Use Case on Art Genre Classification
1 Introduction
2 Preliminaries
2.1 A Formal Framework For Handling Speculations
2.2 Art Genres
3 Logical Deduction and Speculation Regarding Art Genres
3.1 Logical Deduction for Classifying Art Genres
3.2 Speculating on Features Related to Art Genres
3.3 Examples of Speculative Reasoning with Imprecise Information
4 Concluding Remarks and Future Work
References
Fuzzy Sets: A Key Towards Hybrid Explainable Artificial Intelligence for Image Understanding
1 Introduction
2 Image Understanding and Spatial Reasoning
3 Information and Knowledge Representation
4 Reasoning
5 Explanations
6 Discussion
References
Contextual Boosting to Explainable SVM Classification
1 Introduction
2 Preliminaries
3 XSVM@ctx
4 Illustrative Examples
5 Related Work
6 Conclusions
References
SPECIAL SESSION 6: Recent Trends in Mathematical Fuzzy Logics
Ideals in the Two-Sorted Variety of Equational States
1 Introduction
2 Preliminaries
3 Ideals of Equational States
References
Maximal Theories of Product Logic*-4pt
1 Introduction
2 Preliminaries
2.1 Product Algebras and Product Triples
2.2 Maximal Filters of Boolean, MV, and Gödel Algebras
3 Constructing a Product Algebra from a Product Hoop
4 Conclusions
References
Free Product Hoops
1 Introduction
2 Preliminaries
2.1 Free Product Algebras
3 Standard Product Hoop
4 Positive Product Functions
5 Functional Representation of Free Product Hoops
6 Alternative Representation
7 Conclusions
References
A Logic to Reason About f-Indices of Inclusion over Łn
1 Introduction
2 Preliminaries
2.1 The Finite-Valued Łukasiewicz Logic
2.2 The f-Index of Inclusion
3 A Logic to Reason About the f-Index of Inclusions over Łcn
3.1 Syntax and Semantics
3.2 The Logic IŁn: Axiomatic System, Soundness and Completeness
4 Conclusions and Future Work
References
SPECIAL SESSION 7: Fuzzy Graph-Based Models: Theory and Application
Reduction Graph for Minimal Determinization of Fuzzy Automata
1 Introduction
2 Preliminaries
3 Factorization in Divisible Complete Residuated Lattices
4 Determinization of a CFfA
5 Minimality via the Reduction Graph
6 Example
7 Conclusion
References
Finite Nerode Construction for Fuzzy Automata over the Product Algebra
1 Introduction
2 Preliminaries
3 Truncating Fuzzy Languages
4 Crisp-Deterministic Fuzzy Finite Automata Accepting Truncating Fuzzy Languages
5 Conclusion
References
Towards New Types of Weak Bisimulations for Fuzzy Automata Using the Product T-Norm
1 Introduction
2 Preliminaries
2.1 Fuzzy Subsets and Fuzzy Relations
2.2 Fuzzy Languages and Fuzzy Automata
2.3 Weak Bisimulations for Fuzzy Automata
3 Finite Construction of Fuzzy Terminal States
4 -Inclusive and -Equivalent Fuzzy Languages
5 -Weak Bisimulations for Fuzzy Automata
6 Conclusion
References
On Relationships Between Approximate Bisimulations for Fuzzy Graphs and Their Approximation Degrees
1 Introduction
2 Preliminaries
3 Approximate Bisimulations for Fuzzy Graphs
4 Conclusions
References
SPECIAL SESSION 8: New frontiers of Computational Intelligence for Pervasive Healthcare Systems
An Information Extraction Study: Take in Mind the Tokenization!
1 Introduction
2 Related Work
3 Tokenization Analysis - Datasets
4 Inductive Bias
4.1 Experimental Setup
4.2 Results - Discussion
4.3 Similarity Analysis
5 Comparative Study
5.1 Baseline Setup: Frozen Embeddings
5.2 Advanced Setup: End-to-End Training
5.3 Hyphenation Analysis
6 Comparison with SOTA Models
7 Conclusion
References
Early Parkinson's Disease Detection from EEG Traces Using Machine Learning Techniques
1 Introduction
2 Related Work
3 Background
3.1 Statistical Synthetic Index
4 Approach
4.1 Data Description
4.2 Experiment Setting
5 Discussion of Results
6 Conclusion and Future Work
References
Cognitive Assistant for Physical Exercise Monitoring in Hand Rehabilitation
1 Introduction
2 Related Work
3 System Description
3.1 Hardware Description
3.2 Software Description
3.3 Image Acquisition
3.4 Model Training
4 Conclusion
References
Interpretable Neuro-Fuzzy Models for Stress Prediction
1 Introduction
2 Materials and Methods
2.1 Data
2.2 Neuro-Fuzzy System
3 Results and Discussion
4 Conclusions
References
Explainable Deep Ensemble to Diagnose COVID-19 from CT Scans
1 Introduction
2 Background
2.1 Considered Convolutional Neural Networks
2.2 Grad-CAM Technique
3 Related Work
4 Approach
5 Experiment Description
6 Results and Discussion
7 Conclusions
References
SPECIAL SESSION 9: Fuzzy Implication Functions
A Study of Monometrics from Fuzzy Logic Connectives
1 Introduction
1.1 Motivation for and Contributions of This Work
1.2 Outline of This Work
2 Distances from FLCs: A Literature Survey
2.1 From T-Norms
2.2 From T-Norms and T-Conorms
2.3 From Quasi-Copulas
2.4 From Symmetric Differences
2.5 From Fuzzy Implications
3 Lifting the Distance
4 Construction of Monometrics from FLCs
4.1 Yet Another Class of Fuzzy Implications
5 Concluding Remarks
References
Monometrics on Lattice Betweenness Using Fuzzy Implications
1 Introduction
1.1 Motivation for and Contributions of This Work
1.2 Outline of This Work
2 Monometrics on Betweenness Relations
3 Monometrics on Lattice Betweenness
3.1 Monometric on Lattice Betweenness
3.2 Monometric Using Fuzzy Implications
3.3 Metrics Using Fuzzy Implications
4 Betweenness Sets Obtained from a Lattice: A Characterisation
5 Concluding Remarks
References
Fuzzy Implications Using Bandler-Kohout Subproduct
1 Introduction
2 Preliminaries
3 Implications Using T-Norms
4 Implications Using a Conjunction and an Implication
5 Implications Using T-Conorms
6 Conclusions
References
The Form of Fuzzy Implication Functions Satisfying a Multiplicative Sincov's Equation
1 Introduction
2 Preliminaries
3 Previous Characterization Result and Counterexample
4 New Characterization Result
5 Conclusions
References
SPECIAL SESSION 10: New Challenges and Ideas in Statistical Inference and Data Analysis
Improved DE-MC Algorithm with Automated Outliers Detection
1 Introduction
2 DE-MC Algorithm
3 Methods for Outliers Detection and Replacement
4 Modification of the DE-MC Method
4.1 Modified Approach
4.2 Numerical Analysis
5 Conclusions
References
A Specialized Xie-Beni Measure for Clustering with Adaptive Distance
1 Introduction
2 Background
2.1 The Fuzzy C-Means Algorithm
2.2 The Wasserstein Distance
3 A Valitidy Measure: The Xie-Beni Index
3.1 Compactness
3.2 Separability
3.3 XB Index
4 Improvement of VXB
4.1 Improvement of the Compactness Measure
4.2 Improvement of the Separability Measure
4.3 XBMW: A New Xie-Beni Index
5 Numerical Experimentation
5.1 Methodology
5.2 Datasets
5.3 External Evaluation Measure
5.4 Results
6 Conclusion
References
Classification Error in Semi-Supervised Fuzzy C-Means
1 Introduction
2 Semi-Supervised Fuzzy C-Means
3 The Scaling Factor and Its Relationship with the Training Error
4 Experiments on Simulated Data
5 Experiments on Real-Life Data
5.1 Application Example in the Smartphone-Based Classification of Bipolar Disorder Patients
5.2 About Dataset Used for Experiments
5.3 Numerical Results
6 Conclusion and Future Work
References
A New Two-Sample Location Test for Fuzzy Data
1 Introduction
2 Fuzzy Data
3 The Two-Sample Location Problem
4 The Generalized Mann-Whitney Test
5 Simulation Study
6 Conclusions
References
Author Index