Fuzzy Logic in Intelligent System Design

Theory and Applications
 
 
Springer (Verlag)
  • erschienen am 30. September 2017
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  • XI, 422 Seiten
 
E-Book | PDF mit Adobe DRM | Systemvoraussetzungen
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978-3-319-67137-6 (ISBN)
 
This book describes recent advances in the use of fuzzy logic for the design of hybrid intelligent systems based on nature-inspired optimization and their applications in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Based on papers presented at the North American Fuzzy Information Processing Society Annual Conference (NAFIPS 2017), held in Cancun, Mexico from 16 to 18 October 2017, the book is divided into nine main parts, the first of which first addresses theoretical aspects, and proposes new concepts and algorithms based on type-1 fuzzy systems. The second part consists of papers on new concepts and algorithms for type-2 fuzzy systems, and on applications of type-2 fuzzy systems in diverse areas, such as time series prediction and pattern recognition. In turn, the third part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques describing new nature-inspired optimization algorithms that use fuzzy dynamic adaptation of parameters. The fourth part presents emergent intelligent models, which range from quantum algorithms to cellular automata. The fifth part explores applications of fuzzy logic in diverse areas of medicine, such as the diagnosis of hypertension and heart diseases. The sixth part describes new computational intelligence algorithms and their applications in different areas of intelligent control, while the seventh examines the use of fuzzy logic in different mathematic models. The eight part deals with a diverse range of applications of fuzzy logic, ranging from environmental to autonomous navigation, while the ninth covers theoretical concepts of fuzzy models
  • Global Poetics
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  • Literatur- und kulturwissenschaftliche Studien zur Globalisierung
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  • 648
1st ed. 2018
  • Englisch
  • Cham
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  • Schweiz
Springer International Publishing
  • 100
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  • 140 s/w Abbildungen, 100 farbige Tabellen
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  • 140 schwarz-weiße Abbildungen, 100 farbige Tabellen, Bibliographie
  • 37,76 MB
978-3-319-67137-6 (9783319671376)
3319671375 (3319671375)
10.1007/978-3-319-67137-6
weitere Ausgaben werden ermittelt
  • Intro
  • Preface
  • Contents
  • Theoretical Aspects of Fuzzy Logic
  • Can Multi-constraint Fuzzy Optimization Bring Complex Problems in Selecting Optimal Solar Power Generating System into Focus?
  • Abstract
  • 1 Introduction
  • 1.1 Commentary on Solar Power Generating System and Selection
  • 1.2 Objective
  • 2 Case Study
  • 2.1 Expert Knowledgebase
  • 3 Results and Discussion
  • 3.1 Similarity Between Experts
  • 3.2 Multi Constraint Fuzzy Optimization
  • References
  • Relating Fuzzy Set Similarity Measures
  • Abstract
  • 1 Introduction
  • 2 Respects for Similarity
  • 3 Set-Based Similarity
  • 4 Geometric-Based Similarity
  • 5 Relating Set and Geometric Similarity
  • 6 Conclusions
  • References
  • Correlation Measures for Bipolar Rating Profiles
  • Abstract
  • 1 Introduction
  • 2 Finite Bipolar Rating Scales and Bipolar Scoring Functions
  • 3 General Methods of Construction of Correlation Measures on the Set with Involution
  • 4 Correlation Measures on the Set of Bipolar Rating Profiles
  • 5 Conclusions
  • Acknowledgements
  • References
  • Solving Real-World Fuzzy Quadratic Programming Problems by Dual Parametric Approach
  • Abstract
  • 1 Introduction
  • 2 Dual Parametric Approach in Fuzzy Environment
  • 3 Economic Dispatch Problem
  • 3.1 Numerical Results and Analysis
  • 4 Conclusion
  • Acknowledgment
  • References
  • Type-2 Fuzzy Logic
  • A Type-2 Fuzzy Hybrid Expert System for Commercial Burglary
  • Abstract
  • 1 Introduction
  • 2 Fuzzy Systems
  • 3 Problem Description
  • 4 Designing the Type-2 FLS
  • 4.1 Determination of Input and Output Variables
  • 4.2 Feature Selection
  • 4.3 Determination of the Number of Rules and Clustering the Output Space
  • 4.4 Projection of Membership Functions of Output onto Input Spaces
  • 4.5 Tuning the Parameters of Type-1 Membership Functions
  • 4.6 Transformation Type-1 to Interval Type-2 Membership Functions
  • 4.7 Tuning the Parameters of Interval Type-2 Membership Functions
  • 5 The Proposed IT2 Fuzzy Hybrid Expert System
  • 6 Performance Evaluation
  • 7 Conclusion
  • References
  • A Type-2 Fuzzy Expert System for Diagnosis of Leukemia
  • Abstract
  • 1 Introduction
  • 1.1 Leukemia
  • 1.2 Expert System
  • 1.3 Type-2 Fuzzy
  • 2 Literature Review
  • 3 Methodology
  • 3.1 Leukemia Dataset
  • 3.2 Determining the Number of Rules
  • 3.3 The Proposed Type-2 Fuzzy Model
  • 3.4 Performance Evaluation
  • 4 Conclusion
  • References
  • Comparative Study of Metrics That Affect in the Performance of the Bee Colony Optimization Algorithm Through Interval Type-2 Fuzzy Logic Systems
  • Abstract
  • 1 Introduction
  • 2 Background
  • 3 Interval Type-2 Fuzzy Systems
  • 3.1 Fuzzy Logic Controller
  • 4 Proposed Methods
  • 5 Simulations Results
  • 6 Discussion
  • 7 Conclusions
  • References
  • Type-2 Fuzzy Approach in Multi Attribute Group Decision Making Problem
  • Abstract
  • 1 Introduction
  • 2 Basic Concepts of Type2 Fuzzy Sets
  • 2.1 Linguistic Weighted Averaging for T2-FSs
  • 3 Proposed Type-2 Fuzzy Multi Attribute Group Decision Making
  • 4 An Illustrative Example
  • 5 Conclusion
  • References
  • Fuzzy Logic in Metaheuristics
  • A New Approach for Dynamic Mutation Parameter in the Differential Evolution Algorithm Using Fuzzy Logic
  • Abstract
  • 1 Introduction
  • 2 The Differential Evolution Algorithm
  • 3 Methodology
  • 4 Results of the Experiments
  • 5 Conclusions
  • References
  • Study on the Use of Type-1 and Interval Type-2 Fuzzy Systems Applied to Benchmark Functions Using the Fuzzy Harmony Search Algorithm
  • Abstract
  • 1 Introduction
  • 2 Proposed FHS Algorithm
  • 3 Simulation Results
  • 4 Statistical Test
  • 5 Conclusions
  • References
  • Fuzzy Adaptation for Particle Swarm Optimization for Modular Neural Networks Applied to Iris Recognition
  • Abstract
  • 1 Introduction
  • 2 Basic Concepts
  • 2.1 Modular Neural Networks
  • 2.2 Fuzzy Logic
  • 2.3 Particle Swarm Optimization
  • 3 Proposed Method
  • 3.1 Particle Swarm Optimization with Fuzzy Dynamic Parameters Adaptation
  • 3.2 Iris Database
  • 4 Experimental Results
  • 4.1 PSO Without Fuzzy Dynamic Parameters Adaptation
  • 4.2 PSO Without Fuzzy Dynamic Parameters Adaptation
  • 5 Conclusions
  • References
  • A New Metaheuristic Based on the Self-defense Mechanisms of the Plants with a Fuzzy Approach Applied to the CEC2015 Functions
  • Abstract
  • 1 Introduction
  • 2 Coping Techniques of the Plants in the Nature
  • 3 Model Equations
  • 4 Case Study
  • 5 Simulation
  • 6 Conclusions
  • References
  • Fuzzy Chemical Reaction Algorithm with Dynamic Adaptation of Parameters
  • Abstract
  • 1 Introduction
  • 2 The CRA Paradigm
  • 2.1 Elements or Compounds
  • 2.2 Chemical Reactions
  • 2.2.1 Combination Reactions
  • 2.2.2 Decomposition Reactions
  • 2.2.3 Substitution Reactions
  • 2.2.4 Double-Substitution Reactions
  • 3 Simulations and Tests
  • 4 Simulation Results
  • 5 Conclusion
  • Acknowledgment
  • References
  • Methodology for the Optimization of a Fuzzy Controller Using a Bio-inspired Algorithm
  • Abstract
  • 1 Introduction
  • 2 Theoretical Framework
  • 3 Firefly Algorithm
  • 4 Methodology
  • 5 Results
  • 6 Conclusions
  • References
  • Emergent Intelligent Models
  • Cellular Automata Enhanced Quantum Inspired Edge Detection
  • Abstract
  • 1 Introduction
  • 2 Quantum Signal Processing
  • 3 Cellular Automata
  • 4 Methodology
  • 5 Results
  • 6 Discussion and Future Work
  • Acknowledgements
  • References
  • Competitive Hybrid Ensemble Using Neural Network and Decision Tree
  • Abstract
  • 1 Introduction
  • 2 Background
  • 2.1 Diversity and Accuracy in Ensemble Models
  • 2.2 Methods for Generating Diverse Models
  • 2.3 Decision Tree, Neural Network, and Hybrid Ensemble
  • 3 Competitive Hybrid Ensemble
  • 4 Experimental Setup
  • 4.1 Datasets
  • 4.2 Implementation Details
  • 5 Results
  • 6 Conclusion
  • References
  • Speeding Up Quantum Genetic Algorithms in Matlab Through the Quack_GPU V1
  • Abstract
  • 1 Introduction
  • 2 Quantum Computing Overview
  • 3 The Quantum Simulator Architecture
  • 4 Speeding Up QGA Through the Quack_GPU
  • 5 Conclusions
  • Acknowledgements
  • References
  • Evolving Granular Fuzzy Min-Max Regression
  • Abstract
  • 1 Introduction
  • 2 Evolving Fuzzy Min-Max Modeling
  • 2.1 eFMR Modeling
  • 2.2 Learning Algorithm
  • 3 Computational Experiments
  • 3.1 Mackey-Glass
  • 3.2 Box and Jenkins Gas Furnace
  • 4 Conclusion
  • Acknowledgement
  • References
  • Optimization of Deep Neural Network for Recognition with Human Iris Biometric Measure
  • Abstract
  • 1 Introduction
  • 2 Historical Development
  • 3 Proposed Method and Problem Description
  • 4 Optimization of Deep Neural Network with Genetic Algorithm
  • 5 Simulation Results
  • 6 Conclusions
  • References
  • Dynamic Local Trend Associations in Analysis of Comovements of Financial Time Series
  • Abstract
  • 1 Introduction
  • 2 Correlation Coefficient and Time Series Comovements
  • 3 Theoretical Background
  • 4 Results
  • 5 Conclusion
  • Acknowledgment
  • References
  • Fuzzy Logic in Medicine
  • An Expert System Based on Fuzzy Bayesian Network for Heart Disease Diagnosis
  • Abstract
  • 1 Introduction
  • 2 Bayesian Networks
  • 3 Fuzzy Set
  • 4 Fuzzy Bayesian Networks
  • 4.1 Fuzzy Bayesian Equation
  • 4.2 Virtual Evidence
  • 4.3 Fuzzy Probability Distribution
  • 5 Model
  • 5.1 K2 Algorithm
  • 5.2 Pseudo Code of K2 Algorithm
  • 6 Performance Evaluation
  • 6.1 Multi SVM
  • 6.2 MLP
  • 6.3 RBF
  • 6.4 KNN
  • 7 Conclusion
  • References
  • A Hybrid Intelligent System Model for Hypertension Risk Diagnosis
  • Abstract
  • 1 Introduction
  • 2 Literature Review
  • 2.1 Blood Pressure and Hypertension
  • 2.2 Neural Network for a Hypertension Diagnosis
  • 2.3 Fuzzy Logic and Hypertension
  • 2.4 Fuzzy Logic and Pulse
  • 3 Proposed Method
  • 4 Methodology
  • 4.1 Graphical User Interface
  • 5 Results and Discussion
  • 6 Conclusions and Future Work
  • Acknowledgment
  • References
  • Estimation of Population Pharmacokinetic Model Parameters Using a Genetic Algorithm
  • Abstract
  • 1 Introduction
  • 2 Population Pharmacokinetics Models
  • 3 Estimation of Population Parameters
  • 4 Genetic Algorithms
  • 4.1 Genetic Algorithm Operators
  • 5 Methodology
  • 6 Results
  • 7 Conclusion
  • Acknowledgments
  • References
  • Intelligent Control
  • Outdoor Robot Navigation Based on Particle Swarm Optimization
  • Abstract
  • 1 Introduction
  • 2 Particle Swarm Optimization
  • 3 Proposed Approach
  • 4 Mobile Robot Navigation
  • 5 Results
  • 5.1 Simulation Results
  • 5.2 Experimental Results
  • 6 Conclusion
  • References
  • Trajectory Optimization for an Autonomous Mobile Robot Using the Bat Algorithm
  • Abstract
  • 1 Introduction
  • 2 Bat Algorithm
  • 3 The Model Unicycle Mobile Robot
  • 4 Methodology and Results
  • 5 Future Work and Conclusion
  • Acknowledgment
  • References
  • Neural Identifier-Control Scheme for Nonlinear Discrete Systems with Input Delay
  • Abstract
  • 1 Introduction
  • 2 Neural Identification
  • 2.1 Recurrent High Order Neural Network Identification
  • 3 Neural Block Control
  • 4 Results
  • 5 Conclusions
  • Acknowledgments
  • References
  • An Application of Neural Network to Heavy Oil Distillation with Recognitions with Intuitionistic Fuzzy Estimation
  • Abstract
  • 1 Introduction
  • 2 Discussion
  • 3 Conclusion
  • References
  • PID Implemented by a Type-1 Fuzzy Logic System with Back-Propagation Algorithm for Online Tuning of Its Gains
  • Abstract
  • 1 Introduction
  • 2 Mathematical Models
  • 3 Proposed Methodology
  • 4 Results
  • 5 Conclusions
  • References
  • A PID Using a Non-singleton Fuzzy Logic System Type 1 to Control a Second-Order System
  • Abstract
  • 1 Introduction
  • 2 The Logic Scheme of the Used PID Controller
  • 3 The Type-1 SFLS Coupled with the PID Controller
  • 4 Results
  • 5 Conclusions
  • References
  • Fuzzy Multi-Criteria Decision Making and Fuzzy Information Gain Based Automotive Recommender System
  • Abstract
  • 1 Introduction
  • 2 Motivation
  • 3 Fuzzy Topsis (F-TOPSIS) and Fuzzy Information Gain (FIG) for Automotive Recommender System
  • 4 Proposed Methodology
  • 5 Conclusion and Future Work
  • References
  • Fuzzy Logic in Mathematics
  • The Shape of the Optimal Value of a Fuzzy Linear Programming Problem
  • 1 Introduction
  • 2 Results
  • 3 Conclusion
  • References
  • How to Gauge the Accuracy of Fuzzy Control Recommendations: A Simple Idea
  • 1 Formulation of the Problem
  • 2 Main Idea
  • 3 But What Should We Do in the Interval-Valued Fuzzy Case?
  • References
  • ``On-the-fly'' Parameter Identification for Dynamic Systems Control, Using Interval Computations and Reduced-Order Modeling
  • 1 Introduction
  • 2 Background
  • 2.1 Reduced-Order Modeling (ROM)
  • 2.2 Interval Computations
  • 3 Problem Statement and Proposed Approach
  • 4 Experimental Results and Analysis
  • 5 Conclusions
  • References
  • Normalization-Invariant Fuzzy Logic Operations Explain Empirical Success of Student Distributions in Describing Measurement Uncertainty
  • 1 Formulation of the Problem
  • 2 Let Us Use Normalization-Invariant Fuzzy Logic Operations
  • 3 Resulting Derivation of the Student Distributions
  • References
  • Can We Detect Crisp Sets Based Only on the Subsethood Ordering of Fuzzy Sets? Fuzzy Sets and/or Crisp Sets Based on Subsethood of Interval-Valued Fuzzy Sets?
  • 1 Formulation of the Problem
  • 2 What If We Consider [0,1]-Based Fuzzy Sets
  • 3 What If We Consider Interval-Valued Fuzzy Sets
  • References
  • Applications of Fuzzy Logic
  • Two Hybrid Expert System for Diagnosis Air Quality Index (AQI)
  • 1 Introduction
  • 2 Background
  • 2.1 AQI Index
  • 2.2 Case Study
  • 3 Method
  • 3.1 The Structure of Fuzzy System
  • 3.2 Fuzzy Rules
  • 3.3 Membership Functions
  • 4 Validation System
  • 5 Conclusion
  • References
  • Fuzzy Rule Based Expert System to Diagnose Chronic Kidney Disease
  • 1 Introduction
  • 2 Background
  • 3 Chronic Kidney Disease (CKD) Data Set
  • 4 Method
  • 4.1 Design of Fuzzy Expert System
  • 5 Conclusion
  • References
  • A Theory of Event Possibility with Application to Vehicle Waypoint Navigation
  • 1 Introduction
  • 2 Intuitive Rationale
  • 3 Formalization
  • 4 Vehicle Waypoint Navigation
  • 5 Concluding Remarks
  • References
  • Intuitionistic Fuzzy Functional Differential Equations
  • 1 Basic Concepts
  • 1.1 Notations and Definitions
  • 1.2 Locally Lipschitz Intuitionistic Fuzzy Function
  • 2 Existence and Uniqueness
  • 2.1 Local Existence and Uniqueness
  • 2.2 Global Existence and Uniqueness
  • 3 Solving Intuitionistic Fuzzy Delay Differential Equation
  • 4 Applications
  • 4.1 Intuitionistic Fuzzy Differential Equations with Distributed Delay
  • 4.2 Intuitionistic Fuzzy Time-Delay Malthusian Model
  • 5 Conclusion
  • References
  • Theoretical Concepts of Fuzzy Models
  • Defects in the Defuzzification of Periodic Membership Functions on Orthogonal Coordinates and a Solution
  • 1 Introduction
  • 2 Defects in the Defuzzification of the Periodic Membership Function
  • 2.1 Periodic Fuzzy Membership Function
  • 2.2 Non-uniqueness of Defuzzified Value
  • 2.3 Converting Between Circular and Cartesian Coordinates
  • 3 Defuzzification
  • 4 Numerical Examples
  • 4.1 The Case in the Sect.2.2
  • 4.2 The Case that Polar Coordinates Conversion for the Periodic Membership Function Is Unnecessary
  • 4.3 The Case of the Membership Function in Fig.4
  • 5 Conclusions
  • References
  • Taking into Account Interval (and Fuzzy) Uncertainty Can Lead to More Adequate Statistical Estimates
  • 1 Formulation of the Problem: Traditional Statistical Approach to Data Processing is not Always Applicable
  • 2 Case 1, When We Do not Know the Distributions: Enter Interval and Fuzzy Uncertainties
  • 3 Case 2, When We Know (A Good Approximation to) the Probability Distribution of the Measurement Error and We Know an Upper Bound on the Systematic Error
  • 4 Discussion
  • References
  • Weak and Strong Solutions for Fuzzy Linear Programming Problems
  • 1 Introduction and Motivation
  • 2 Basics on Fuzzy Numbers
  • 3 Linear Programming with Fuzzy Parameters
  • 3.1 Weak and Strong Solutions for FLPs
  • 3.2 Compact, Unbounded Solutions
  • 4 Application Examples
  • 5 Concluding Remarks
  • References
  • Fuzzy Restricted Boltzmann Machines
  • 1 Introduction
  • 2 Algorithm and Implementation
  • 2.1 General Algorithm
  • 2.2 Crisp Multiclass Algorithm
  • 2.3 Fuzzy Multiclass Algorithm
  • 3 Results
  • References
  • Exotic Semirings and Uncertainty
  • 1 Introduction
  • 2 Semirings
  • 2.1 Constructing New Semirings from Old
  • 3 Additivity and Semirings
  • 4 Information Measures and Additivity
  • 5 Ricardian Trade
  • 5.1 Tropical Geometry
  • 6 The Fuzzy Semirings
  • 7 Conclusion
  • References
  • Restricted Equivalence Function on L([0,1])
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 Aggregation Functions
  • 2.2 Fuzzy Implications
  • 2.3 Restrited Equivalence Functions
  • 2.4 Interval Fuzzy Negations and Implications
  • 3 Restricted Equivalence Functions on L([0,1])
  • 3.1 Admissible Orders on Lattice L([0,1])
  • 3.2 Interval Restricted Equivalence Functions
  • 4 Final Remarks
  • References
  • Author Index

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