Applications of Fuzzy Techniques

Name: Applications of Fuzzy Techniques | Proceedings of the 2022 Annual Conference of the North American Fuzzy Information Processing Society NAFIPS 2022
Brand: Springer
Price: 149.79 EUR
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Proceedings of the 2022 Annual Conference of the North American Fuzzy Information Processing Society NAFIPS 2022

Scott Dick Vladik Kreinovich Pawan Lingras(Herausgeber*in)

Springer (Verlag)

Erschienen am 29. September 2022

IX, 366 Seiten

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978-3-031-16038-7 (ISBN)

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Inhalt

Intro
Preface
Contents
How to Elicit Complex-Valued Fuzzy Degrees
1 Formulation of the Problem
2 Analysis of the Problem
3 So How to Elicit Complex-Valued Fuzzy Degrees: Algorithm and Discussion
4 Conclusions
References
Flutter Mitigation via Fuzzy Gain Scheduling of a Passivity-Based Controller
1 Introduction
1.1 Problem
1.2 Genetic Fuzzy Control
1.3 Benchmark Aerodynamic Controls Technology Model
2 Methodology
2.1 Standard Controller
2.2 Fuzzy Gain Scheduled Controller
3 Results and Discussion
4 Conclusions
References
A New Weighting Method in Fuzzy Multi-criteria Decision Making: Selected Element Reduction Approach (SERA)
1 Introduction
2 Preliminaries
3 Methodology
4 Application
5 Conclusion
References
Genetic Fuzzy System for Pitch Control on a F-4 Phantom
1 Introduction
2 F-4 Fighter Pitch Angle Dynamic Behavior
3 Genetic Takagi-Sugeno-Kang Fuzzy Inference System
4 Conclusions and Future Works
References
Analyzing the Sars-Cov-2 Pandemic Outbreak Using Fuzzy Sets and the SIR Model
1 Introduction
2 The Sars-Cov-2 Pandemic
3 Basic Concepts on Fuzzy Sets
4 SIR Model
4.1 Fuzzy Solution and Asymptotic Behavior
4.2 Time-Varying Basic Reproductive Number
5 Application to Sars-Cov-2 Outbreak
5.1 Results
5.2 Comparing and Forecasting
6 Conclusion
References
Hybrid Fuzzy-LQR Control for Time Optimal Spacecraft Docking
1 Introduction
1.1 Related Work
2 Background
2.1 Linear Quadratic Regulator Control
2.2 Fuzzy-Based Bang-Bang Control
2.3 Genetic Algorithms
3 Methodology
3.1 Spacecraft Docking Problem
3.2 GA Approach
3.3 LQR Controller Approach
3.4 Fuzzy-Based Bang-Bang Controller Approach
3.5 Hybrid Fuzzy-LQR Controller Approach
4 Results
5 Conclusion
References
An Experimental Study on Fuzzy Markov Chains Under Mn Generalized Mean Relation
1 Introduction and Motivation
2 Fuzzy Markov Chains
2.1 Normalized Fuzzy Transition Matrix
2.2 Mn Generalized Mean and Its Use in Computing the Limiting Distribution of P
3 Illustrative Examples
3.1 Discussion of the Results
4 Concluding Remarks
References
An Approach to Simulation of Fuzzy Linguistic Variables
1 Introduction and Motivation
2 Basics on Fuzzy Numbers
2.1 Fuzzy Linguistic Variables
3 An Approach to Fuzzy Linguistic Random Variate Generation
3.1 Fuzzy Random Variate Generation for Linguistic Variables
3.2 Fuzzy Random Linguistic Value Generation
3.3 Fuzzy Random Variate Generation
4 Illustrative Example
5 Concluding Remarks
References
Why Sine Membership Functions
1 Formulation of the Problem
2 Our Explanation
3 Conclusions
References
Agricultural Yield Prediction by Difference Equations on Data-Induced Cumulative Possibility Distributions
1 Introduction
2 Mathematical Background
2.1 Elementary Lattice Theory Definitions
2.2 The Cone of Intervals' Numbers (INs) and a Novel Interpretation
2.3 Differential Intervals' Number (IN) Models
3 Novel Algorithms
3.1 Difference Intervals' Number (IN) Models
3.2 Algorithms for Training and Testing
4 Experiments and Results
4.1 Data Acquisition
4.2 Data Preprocessing and Experiments
4.3 Discussion
5 Conclusion
References
Commonsense-Continuous Dynamical Systems - Stationary States, Prediction, and Reconstruction of the Past: Fuzzy-Based Analysis
1 Formulation of the Problem
2 Mathematical Continuity vs. Commonsense Continuity: Analysis of the Difference
3 Useful Corollary
4 Auxiliary Corollaries: Predicting the Future and Reconstructing the Past
5 Conclusions
References
Why Gaussian Copulas Are Ubiquitous in Economics: Fuzzy-Related Explanation
1 Formulation of the Problem
2 Analysis of the Problem and the Resulting Explanation
References
A Note on Caputo Fractional Derivative in the Space of Linearly Correlated Fuzzy Numbers
1 Introduction
2 Preliminaries
2.1 Interactivity
2.2 The Space RF(A)
3 Caputo Derivative in RF(A)
4 Fractional Logistic Model in RF(A) for Cumulative Cases of COVID-19
5 Conclusion
References
Data Driven Level Set Method in Fuzzy Modeling and Forecasting
1 Introduction
2 Data Driven Level Set Method
3 Model Accuracy and Transparency
4 Electric Power Load Forecasting
5 Conclusion
References
Semi-supervised Physics-Informed Genetic Fuzzy System for IoT BLE Localization
1 Introduction
2 Background
3 Dataset Description
4 Methodology
4.1 Semi-supervised Label Propagation
4.2 Physics-Informed Genetic Fuzzy System
5 Results and Discussion
6 Conclusion
References
The Constraint Interval Theory: A Solution for Interval Differential Equations
1 Introduction
2 Standard Interval Arithmetic and Constraint Interval Arithmetic
3 Solution of Initial Value Problem for Interval Linear Differential Equations System
4 Conclusion
References
Classification of Rice Using Genetic Fuzzy Cascading System
1 Introduction
1.1 Need of Fuzzy Techniques for Explainable AI (XAI)
1.2 Genetic Fuzzy Systems and Cascading
1.3 Classification of Rice
2 Methodology
2.1 Fuzzy Inference System (FIS)
2.2 Fuzzy Cascading
2.3 Genetic Algorithm
3 Results
4 Conclusion
4.1 Challenges and Future Work
References
On a New Contrapositivisation Technique for Fuzzy Implications Constructed from Grouping Functions
1 Introduction
2 Preliminaries
3 Contrapositivisation Techniques
4 (G,N)-Contrapositivisation
5 Final Remarks
References
Genetically Trained Fuzzy Cognitive Maps for Effects Based Operations
1 Introduction
2 Methodology
2.1 Forward Propagating Knowledge Graph Solution
2.2 Genetic Source-Determination Knowledge Graph Solution
2.3 Fuzzy Inference System Integration
3 Results and Discussion
3.1 Forward Propagating Solver Results
3.2 Genetic Source-Determination Results
4 Conclusions and Future Work
References
Genetic Fuzzy Controller for the Homicidal Chauffeur Differential Game
1 Introduction
1.1 Related Work on the Homicidal Chauffeur
2 Methodology
2.1 Optimal Control Solution
2.2 Genetic Fuzzy System
2.3 Noise Addition
3 Results
3.1 Results of Noise Added
4 Discussion
5 Summary and Conclusions
References
Use of Fuzzy PID Controller for Pitch Control of a Wind Turbine
1 Introduction
2 Background and Preliminaries
2.1 Wind Turbine Model
2.2 Genetic Algorithm
2.3 Genetic Fuzzy System
3 Methodology
4 Results
5 Conclusion and Future Works
References
Special Tolerance Left Solution for Course Assignment Problem with Interval Workload Constraint
1 Introduction
2 Special Tolerance Left Solution to System of Interval Linear Equations
2.1 Definition and Characteristics of Tolerance Solution to System of Interval Linear Equations
2.2 Definition and Characteristics of Special Tolerance Left Solution to System of Interval Linear Equations
3 Course Assignment Problem with Interval Workload Constraint
4 Results
5 Conclusion
References
Passive Fault-Tolerant Control Scheme for Nonlinear Level Control System with Parameter Uncertainty and Actuator Fault
1 Introduction
2 Uncertain Benchmark Level Control System
2.1 Uncertain Benchmark Two-Tank Level Control System
2.2 Benchmark Two-Tank Level Control System Mathematical Modeling
3 Proposed Methodology for Passive FTC
3.1 Data Generation Layer
3.2 Pre-processing Layer
3.3 Training Layer
4 Implementation and Results
4.1 Implementation Setup
4.2 Simulation Results
5 Conclusion and Future Work
References
Can Physically-Trained Genetic Fuzzy Learning Algorithm Improve Pitch Control in Wind Turbines?
1 Introduction
2 WT Model
3 Genetic Fuzzy Methodology
3.1 Genetic Algorithm
3.2 Training the GFS
3.3 Structure of the GFS
4 Results
4.1 Training the GFS
4.2 Testing the GFS
5 Conclusions and Future Work
References
Generating Interval Type-2 Fuzzy Inputs from Smoothed Data for Fuzzy Rule-Based Systems
1 Introduction
2 Some Background Information
2.1 Type-1 and Type-2 Fuzzy Sets
2.2 Non-Singleton Fuzzy Logic Systems
2.3 Smoothing Using Penalized Least Squares Regression
2.4 Signal-to-Noise Ratio
3 Problem Statement and Methodology
3.1 Algorithm 1: Stable Noise in Both Training and Test Sets
3.2 Algorithm 2: Varying Noise Levels in the Application Phase
4 Experimental Results in Time Series Prediction
5 Concluding Remarks
References
Subsethood Measures on a Bounded Lattice of Continuous Fuzzy Numbers with an Application in Approximate Reasoning
1 Introduction
2 Some Mathematical Background on Lattice Theory and Subsethood Measures
3 Some Facts Regarding Subsethood and Inclusion Measures
4 A Bounded Lattice of Continuous Fuzzy Numbers for Analogical Reasoning
5 An Outline of an Application in Mechanical Condition Monitoring
6 Conclusions
References
Why Ideas First Appear in Informal Form? Why It Is Very Difficult to Know Yourself? Fuzzy-Based Explanation
1 Formulation of the Problem
2 Analysis of the Problem Explains the Need for Informal Ideas
3 From This Viewpoint, Measurement Errors Are the Blessing in Disguise
4 Why Is It Difficult to Know Oneself
5 How Can All This Be Used
References
Pulsar Candidate Selection Using a Genetic Fuzzy System
1 Introduction
2 Background
2.1 Pulsar Candidate Generation
2.2 Pulsar Candidate Selection
2.3 Pulsar Data Set
3 Methodology
3.1 Genetic Fuzzy Tree
3.2 Genetic Algorithm
3.3 Training and Testing
4 Results and Discussion
5 Conclusions
References
Single Hidden Layer CEFYDRA: Cluster-first Explainable FuzzY-based Deep self-Reorganizing Algorithm
1 Introduction
2 Introduction of the Architecture
3 Update Rules for Hidden Layer Parameters
4 Conclusions
References
Multiple Hidden Layered CEFYDRA: Cluster-First Explainable Fuzzy-Based Deep Self-reorganizing Algorithm
1 Introduction
2 On the Learning Formulas for the Hidden Layer
3 On How to Perform the Update While Minimizing the Calculations
4 Conclusions
References
Initialization and Plasticity of CEFYDRA: Cluster-first Explainable FuzzY-based Deep self-Reorganizing Algorithm
1 Introduction
2 On How to Initialize the Parameters Without Prior Knowledge of the Hidden Features
2.1 Initialization of the Cauchy Membership Functions
2.2 Initialization of the Logistic Functions
3 On the Plasticity of CEFYDRA
4 Conclusions
References
Synthesis Chemical Reaction Model via P-Fuzzy Systems
1 Introduction
2 Method
2.1 Fuzzy Rule-Based System
2.2 Partially Fuzzy System
3 Application
4 Final Remarks
References
Proposal of a Novel Python-Based Fuzzy Systems Library - Preliminary Results
1 Introduction
2 Related Work
3 Preliminaries
3.1 Fuzzy Systems
3.2 Mamdani to Takagi-Sugeno-Kang Representation
3.3 Mamdani Approximation of a TSK System. One Antecedent Case
3.4 Mamdani Approximation of a TSK System. Multiple Antecedent Case
4 Library Description
4.1 Architecture Overview
4.2 Defining Membership Functions, Groups, and Groupsets
4.3 Defining Rules and Rulesets
4.4 Performing Mamdani and Takagi-Sugeno-Kang Inference
4.5 Fuzzy Network Definition and Evaluation
4.6 Approximating Mamdani Membership Functions
5 Examples
5.1 Temperature
5.2 Tipping
6 Conclusion and Further Research
References
Author Index

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