| Autore |
Rayz Julia
|
| Pubbl/distr/stampa |
Cham : , : Springer International Publishing AG, , 2021
|
| Descrizione fisica |
1 online resource (519 pages)
|
| Altri autori (Persone) |
RaskinVictor
DickScott
KreinovichVladik
|
| Collana |
Lecture Notes in Networks and Systems Ser.
|
| Soggetto genere / forma |
Electronic books.
|
| ISBN |
3-030-82099-8
|
| Formato |
Materiale a stampa  |
| Livello bibliografico |
Monografia |
| Lingua di pubblicazione |
eng
|
| Nota di contenuto |
Intro -- Explainability: New Application and New Promise of Fuzzy Techniques -- Contents -- A Fuzzy Logic Approach for Spacecraft Landing Site Selection -- 1 Introduction -- 2 Image Dataset -- 3 Methodology -- 3.1 Image Size Reduction -- 3.2 Object Grouping -- 3.3 Object Classification -- 3.4 Performance Metrics -- 4 Results -- 5 Conclusions and Future Work -- 5.1 Future Work -- References -- Takagi-Sugeno Fuzzy Systems with Triangular Membership Functions as Interpretable Neural Networks -- 1 Introduction -- 2 Preliminaries -- 2.1 Fuzzy Systems -- 2.2 Neural Networks -- 3 Equivalence Between TS Fuzzy Systems with Triangular Membership And Neural Networks with ReLU Activation -- 3.1 TS Fuzzy Systems Expressed in Terms of ReLU Functions -- 3.2 TS Fuzzy Systems as Neural Networks with ReLU Activation -- 3.3 Neural Networks Expressed in Terms of Takagi-Sugeno Fuzzy Systems -- 4 Conclusions -- References -- A Study on Constrained Interval Arithmetic -- 1 Introduction -- 2 Constrained Interval Arithmetic -- 2.1 Addition in CIA -- 2.2 Difference in CIA -- 2.3 Multiplication in CIA -- 2.4 Division in CIA -- 2.5 Additive/Multiplicative Inverse in CIA -- 3 Distributivity, Expression/component-Wise and Optimization -- 4 Inclusion Isotonicity -- 5 Final Remarks -- References -- Fuzzy Classification of Multi-intent Utterances -- 1 Introduction -- 2 Related Work -- 3 Utterance Level Fuzzy Memberships -- 3.1 Membership Functions -- 3.2 Parameter Generation -- 4 Single Intent to Multi Intent Utterances -- 5 Fuzzy Membership Aggregation and Defuzzification -- 6 Experiments -- 6.1 Setup -- 6.2 Data -- 6.3 Training Details -- 6.4 Results -- 7 Conclusion -- References -- How Much for a Set: General Case of Decision Making Under Set-Valued Uncertainty -- 1 Decision Making Under Set-Valued Uncertainty: Formulation of the Problem.
2 What Is Known: Cases of Closed Intervals and Closed Sets -- 3 Extending the Known Result to General Bounded Sets -- 4 What if We Do Not Require Additivity? -- Reference -- A Deep Fuzzy Semi-supervised Approach to Clustering and Fault Diagnosis of Partially Labeled Semiconductor Manufacturing Data -- 1 Introduction -- 2 Methodology -- 2.1 Deep Convolutional Unsupervised Feature Learning -- 2.2 PCA-Based Semi-supervised Fault Classification -- 2.3 Fuzzy c-means Clustering and Borderline Case Detection -- 3 Results -- 3.1 Case Study Description -- 3.2 Semi-supervised Classification Results -- 3.3 Fuzzy c-means Clustering Results -- 4 Discussion -- 5 Conclusion -- References -- Why Fuzzy Techniques in Explainable AI? Which Fuzzy Techniques in Explainable AI? -- 1 Why Fuzzy Techniques in Explainable AI -- 2 Which Fuzzy Techniques in Explainable AI -- References -- Why Are Fuzzy and Stochastic Calculus Different? -- 1 Introduction -- 2 Introduction to Stochastic Equations and First Issues with Derivatives -- 3 Modes of Convergence -- 4 Convergence in Distribution -- 5 Is Weakening the Topology a Viable Solution? -- 6 Comparison with Fuzzy Calculus. Common Problems and Conclusion -- References -- A Genetic Fuzzy Approach for the Prediction of Heart Failure -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- COVID-19 Vaccination Priority Evaluation -- 1 Introduction -- 2 The Vaccination Priority Degree and Its Use -- 3 The Vaccination Priority Attribute Tree -- 4 Vaccination Priority Attribute Criteria -- 5 Logic Aggregation -- 6 Examples and Discussion -- 7 Conclusions -- References -- Comparing the Explainability and Performance of Reinforcement Learning and Genetic Fuzzy Systems for Safe Satellite Docking -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Run Time Assurance.
3.2 Reinforcement Learning Approach -- 3.3 Genetic Fuzzy System Approach -- 3.4 Run Time Assurance Approach -- 3.5 Reward Function -- 4 Results -- 4.1 Training -- 4.2 Explainability -- 5 Conclusion -- References -- A Note on the KM Algorithm for Computing the Variance of an Interval Type-2 Fuzzy Set -- 1 Introduction and Motivation -- 2 Basics of Interval Type-2 Fuzzy Numbers -- 3 The KM Algorithm -- 3.1 a) KM Algorithm for Computing yl -- 3.2 b) KM Algorithm for Computing yr -- 4 Computing the Variance of F2(X) -- 5 Illustrative Examples -- 5.1 Trapezoidal IT2FS -- 5.2 Nonlinear IT2FS -- 6 Concluding Remarks -- References -- Estimating Fuzzy Possibility Functions for E-Commerce Decision Support -- 1 Introduction -- 2 Methodology -- 2.1 Data Experiments -- 2.2 Linguistic Pre-processing -- 2.3 Feature Extraction and Statistical Methods -- 2.4 Model Evaluation -- 3 Soft Business Function -- 4 Results -- 5 Final Remarks -- References -- Machine Learning to Augment the Fusion Process for Data Classification -- 1 Introduction -- 2 Dempster-Shafer Fusion -- 3 Q-Learning -- 3.1 Q-Learning Fundamentals -- 3.2 Dempster-Shafer Fusion Calculus Integrated into Q-Learning -- 4 Experiments -- 5 Conclusions and Future Research -- References -- Managing Uncertainty in Crowdsourcing with Interval-Valued Labels -- 1 Introduction -- 1.1 Uncertainties in Crowdsourcing -- 1.2 Previous Results and Motivations of This Study -- 2 Interval-Valued Labels and Their Properties -- 2.1 An Interval-Valued Label and Its Properties -- 2.2 Statistic and Probabilistic Properties of a Set of IVLs on the Same xi -- 3 Methods for Pre-processing IVLs and Inference Making -- 3.1 Strategies on Pre-processing Li -- 3.2 Making an Inference from Li -- 4 Computational Experiments -- 4.1 Comparisons of Inferences with MV and Algorithm2 from the Same Li.
4.2 Impacts of Biased IVLs on the Distribution of Matching Probability -- 5 Summary -- References -- Modeling Fuzzy Cluster Transitions for Topic Tracing -- 1 Introduction -- 2 Related Work -- 3 Modeling Cluster Transition with Fuzzy Logic -- 3.1 Crisp Cluster Transitions for Topic Tracing -- 3.2 Fuzzified Cluster Transitions -- 4 Implementation: Comparing Crisp and Fuzzy Cluster Transitions -- 5 Conclusion -- References -- A Natural Formalization of Changing-One's-Mind Leads to Square Root of ``Not'' and to Complex-Valued Fuzzy Logic -- 1 Formulation of the Problem -- 2 Analysis of the Problem and the Resulting Derivation of Square Root of ``Not" and of Complex-Valued Fuzzy Logic -- References -- Each Realistic Continuous Functional Dependence Implies a Relation Between Some Variables: A Theoretical Explanation of a Fuzzy-Related Empirical Phenomenon -- 1 Formulation of the Problem -- 2 Formalization of the Problem -- 3 Main Result -- 4 Auxiliary Result: Case of m=1 -- References -- Uniform Mixture Convergence of Continuously Transformed Fuzzy Systems -- 1 Rule-Based Probability Mixtures and XAI -- 2 Probability Structure of Additive Fuzzy Rule-Based Systems -- 3 Uniform Convergence of Mixtures of Transformed Fuzzy Systems -- 4 Conclusions -- References -- Solutions of Systems of Linear Fuzzy Differential Equations for a Special Class of Fuzzy Processes -- 1 Introduction -- 2 Mathematical Background -- 3 Calculus Theory for Fuzzy Functions Under -derivative -- 4 Systems of Linear FDEs for S-linearly Correlated Fuzzy Processes -- 5 Application on Mass-Spring Multiple System -- 6 Final Remarks -- References -- Abstractive Representation Modeling for Image Classification -- 1 Introduction -- 1.1 Background -- 1.2 Identified Research -- 2 Data -- 2.1 MNIST Digit Dataset -- 3 Method -- 3.1 Abstractive Processing -- 3.2 Abstractive Level Design.
3.3 Pattern Frequency Detector -- 3.4 Classifier -- 4 Results -- 4.1 Global Performance Analysis of ARM and CNN -- 4.2 Robustness Analysis of ARM and CNN -- 5 Conclusion -- 5.1 Contributions -- 5.2 Future Research -- References -- A-Cross Product for Autocorrelated Fuzzy Processes: The Hutchinson Equation -- 1 Introduction -- 2 Fuzzy Set Theory -- 3 A-cross Product of Linearly Correlated Fuzzy Numbers -- 4 Fuzzy Differential Equations Under Fréchet Derivative -- 5 The Hutchinson Equation -- 5.1 Crisp Logistic Growth Rate -- 5.2 Fuzzy Logistic Growth Rate -- 6 Final Considerations -- References -- Use of T-Norm in an Epidemiological Model for COVID-19 -- 1 Introduction -- 1.1 Triangular Norm and SIR Model -- 2 Methodology -- 3 Application and Results -- 4 Comments and Discussions -- 5 Conclusion -- References -- Fuzzy-Flatness Hybrid Fault-Tolerant Control -- 1 Introduction -- 2 Differential Flatness -- 3 3-Tank Problem -- 4 Fuzzy-Flatness Hybrid Control -- 5 Results -- 6 Conclusion -- References -- Finding Fuzziness in Neural Network Models of Language Processing -- 1 Introduction -- 2 The Concept of Vagueness and the Vagueness of Concepts -- 2.1 Psychological Significance -- 2.2 Handling Vagueness Using Fuzzy Interpretations of Linguistic Hedges -- 3 Pre-trained Language Models -- 4 Vagueness in Natural Language Inference Models -- 4.1 Methodology -- 5 General Discussion and Conclusion -- References -- Interval Arithmetic: WSM, CI or RDM? -- 1 Introduction -- 2 CIA and RDM Arithmetics -- 2.1 Fuzzy Interval Linear Systems -- 3 Conclusion -- References -- Breast Cancer Wisconsin (Diagnostic) Data Analysis Using GFS-TSK -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusions -- References -- A New GA-PSO Optimization Methodology with Fuzzy Adaptive Inertial Weight -- 1 Introduction -- 2 Proposed Optimization Methodology.
2.1 Parents Selection Genetic Operator.
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| Altri titoli varianti |
Explainable AI and Other Applications of Fuzzy Techniques
|
| Record Nr. | UNINA-9910497106303321 |
Info
Explainable AI and Other Applications of Fuzzy Techniques : Proceedings of the 2021 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2021
