Abbildung von: Advances in Fuzzy Logic and Technology 2017 - Springer

Advances in Fuzzy Logic and Technology 2017

Proceedings of: EUSFLAT- 2017 - The 10th Conference of the European Society for Fuzzy Logic and Technology, September 11-15, 2017, Warsaw, Poland IWIFSGN'2017 - The Sixteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, September 13-15, 2017, Warsaw, Poland, Volume 3
Erschienen am 29. August 2017
XI, 602 Seiten
E-Book
PDF mit Wasserzeichen-DRM
978-3-319-66827-7 (ISBN)
213,99 €inkl. 7% MwSt.
Systemvoraussetzungen
für PDF mit Wasserzeichen-DRM
E-Book Einzellizenz
Als Download verfügbar

This volume constitutes the proceedings of two collocated international conferences: EUSFLAT-2017 - the 10th edition of the flagship Conference of the European Society for Fuzzy Logic and Technology held in Warsaw, Poland, on September 11-15, 2017, and IWIFSGN'2017 - The Sixteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, held in Warsaw on September 13-15, 2017. The conferences were organized by the Systems Research Institute, Polish Academy of Sciences, Department IV of Engineering Sciences, Polish Academy of Sciences, and the Polish Operational and Systems Research Society in collaboration with the European Society for Fuzzy Logic and Technology (EUSFLAT), the Bulgarian Academy of Sciences and various European universities.

The aim of the EUSFLAT-2017 was to bring together theoreticians and practitioners working on fuzzy logic, fuzzy systems, soft computing and related areas and to provide a platform for exchanging ideas and discussing the l

atest trends and ideas, while the aim of IWIFSGN'2017 was to discuss new developments in extensions of the concept of a fuzzy set, such as an intuitionistic fuzzy set, as well as other concepts, like that of a generalized net. The papers included, written by leading international experts, as well as the special sessions and panel discussions contribute to the development the field, strengthen collaborations and intensify networking.

Reihe
Auflage
1st ed. 2018
Sprache
Englisch
Verlagsort
Cham
Schweiz
Verlagsgruppe
Springer International Publishing
Illustrationen
143 s/w Abbildungen
XI, 602 p. 143 illus.
Dateigröße
41,00 MB
ISBN-13
978-3-319-66827-7 (9783319668277)
DOI
10.1007/978-3-319-66827-7
Schlagworte
Schweitzer Klassifikation
Thema Klassifikation
DNB DDC Sachgruppen
Dewey Decimal Classfication (DDC)
BIC 2 Klassifikation
BISAC Klassifikation
Warengruppensystematik 2.0
  • Intro
  • Foreword
  • Contents
  • Higher Degree Fuzzy Transform: Application to Stationary Processes and Noise Reduction
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 Basic Concepts of Stationary Processes
  • 2.2 Generalized Uniform Fuzzy Partition
  • 3 Higher Degree Fuzzy Transform Applied to Stationary Processes
  • 3.1 Direct Fm-Transform
  • 3.2 Inverse Fm-Transform
  • 4 Reduction of Noise
  • 5 Illustrative Examples
  • 6 Conclusions
  • References
  • Sheffer Stroke Fuzzy Implications
  • 1 Introduction
  • 2 Preliminaries
  • 3 Sheffer Stroke Implications
  • 3.1 SSpq-Implications
  • 3.2 SSqq-Implications
  • 4 Basic Properties of Sheffer Stroke Implications
  • 5 Conclusions
  • References
  • Towards Fuzzy Type Theory with Partial Functions
  • 1 Introduction
  • 2 Truth Values and Fuzzy Equality
  • 2.1 Truth Values
  • 2.2 Extended Algebra of Truth Values
  • 2.3 Fuzzy Equality
  • 3 Syntax of Partial FTT
  • 3.1 Axioms and Inference Rules
  • 3.2 Logical Connectives and the ``undefined''
  • 4 Semantics of Partial FTT
  • 5 Canonical Model of Partial FTT
  • 5.1 Extension of Theories
  • 5.2 Canonical Frame and Completeness
  • 6 Partial Functions
  • 7 Conclusion
  • References
  • Dynamic Intuitionistic Fuzzy Evaluation of Entrepreneurial Support in Countries
  • Abstract
  • 1 Introduction
  • 2 Entrepreneurial Support
  • 3 Dynamic Intuitionistic Fuzzy Evaluation
  • 3.1 Preliminaries
  • 3.2 Dynamic Intuitionistic Fuzzy Evaluation Method
  • 4 Entrepreneurial Support Evaluation
  • 5 Conclusion
  • References
  • Hesitant Fuzzy Evaluation of System Requirements in Job Matching Platform Design
  • Abstract
  • 1 Introduction
  • 2 Current Studies on Requirements Prioritization
  • 3 Hesitant Fuzzy Multi-criteria System Requirements Evaluation
  • 3.1 Preliminaries
  • 3.2 Steps of the Methodology
  • 4 Application
  • 5 Conclusion
  • References
  • An Interval Valued Hesitant Fuzzy Clustering Approach for Location Clustering and Customer Segmentation
  • Abstract
  • 1 Background
  • 2 Related concepts
  • 2.1 Location Based Mobile Advertising
  • 2.2 Location Based Clustering
  • 3 Motivation
  • 4 Methodology
  • 4.1 Preliminaries
  • 4.2 Fuzzy c means clustering
  • 4.3 Interval Valued Hesitant Fuzzy c means clustering
  • 5 Application
  • 6 Conclusion
  • References
  • Aggregation of Risk Level Assessments Based on Fuzzy Equivalence Relation
  • 1 Introduction
  • 2 Upper General Aggregation Operator Based on a Fuzzy Equivalence Relation
  • 3 Upper General Aggregation Operator in Risk Level Assessments
  • 4 Fuzzy Equivalence Relation Based on a Metric
  • 5 Aggregation of Experts' Evaluations of Countries Risk Level
  • 6 Conclusion
  • References
  • Six Sigma Project Selection Using Interval Neutrosophic TOPSIS
  • Abstract
  • 1 Neutrosophic Sets in Multicriteria Decision Making
  • 2 Preliminaries of Neutrosophic Sets
  • 2.1 Arithmetic Operations with Neutrosophic Sets
  • 2.2 Arithmetic Operations with Interval Neutrosophic Sets
  • 3 Neutrosophic TOPSIS with Group Decision Making
  • 4 Application
  • 5 Conclusion
  • References
  • Integrated Call Center Performance Measurement Using Hierarchical Intuitionistic Fuzzy Axiomatic Design
  • Abstract
  • 1 Introduction
  • 2 Methodology
  • 2.1 Intuitionistic Fuzzy Sets
  • 2.2 Information Axiom
  • 2.3 Hierarchical Intuitionistic Fuzzy Axiomatic Design
  • 3 Application
  • 3.1 Decision Model
  • 3.2 Call Center Performance Measurement
  • 4 Conclusion
  • References
  • Prioritization of Business Analytics Projects Using Interval Type-2 Fuzzy AHP
  • Abstract
  • 1 Introduction
  • 2 Methodology
  • 2.1 Interval Type-2 Fuzzy Sets
  • 2.2 Interval Type-2 Fuzzy AHP
  • 3 Application
  • 3.1 Background of the Case Study
  • 3.2 Decision Model
  • 3.3 Prioritization of the Alternatives
  • 4 Conclusion
  • References
  • Optimized Fuzzy Transform for Image Compression
  • 1 Introduction
  • 2 Fuzzy Transform of Discrete Functions
  • 3 The Gravitational Search Algorithm
  • 4 GSA for Tuning the Fuzzy Partition of the Fuzzy Transform
  • 5 Experimental Results
  • 6 Conclusions
  • References
  • Fuzzy Decision Matrices in Case of a Discrete Underlying Fuzzy Probability Measure
  • 1 Introduction
  • 2 Fuzzy Decision Matrices Viewed as a Collection of Fuzzy Rule-Based Systems
  • 3 Fuzzy Decision Matrix in the Case of Underlying Discrete Fuzzy Probability Measure
  • 4 Illustrative Example
  • 5 Conclusion
  • References
  • Compositions Consistent with the Modus Ponens Property Used in Approximate Reasoning
  • 1 Introduction
  • 2 Preliminaries
  • 3 General Modus Ponens Property
  • 4 Algorithm for Interval-Valued Multiconditional Approximate Reasoning
  • 5 Conclusions and Future Research
  • References
  • General Preference Structure with Uncertainty Data Present by Interval-Valued Fuzzy Relation and Used in Decision Making Model
  • 1 Introduction
  • 2 Preliminaries
  • 3 Preference Structure
  • 4 Application
  • 5 Conclusion
  • References
  • Comparative Study of Type-1 and Interval Type-2 Fuzzy Systems in the Fuzzy Harmony Search Algorithm Applied to Benchmark Functions
  • Abstract
  • 1 Introduction
  • 2 Proposed FHS Algorithm
  • 3 Simulation Results
  • 4 Conclusions
  • References
  • Penalty-Based Aggregation Beyond the Current Confinement to Real Numbers: The Method of Kemeny Revisited
  • 1 Introduction
  • 2 Penalty Functions in the Setting of Real Numbers
  • 3 The Extension Beyond the Setting of Real Numbers
  • 4 The Framework of the Aggregation of Rankings
  • 5 A Prominent Example of Penalty-Based Aggregation Outside the Setting of Real Numbers: The Method of Kemeny
  • 6 Conclusions
  • References
  • Is Fuzzy Number the Right Result of Arithmetic Operations on Fuzzy Numbers?
  • 1 Introduction
  • 2 Relationship Between Fuzzy and Interval Arithmetic
  • 3 What Is the Result of Arithmetic Operations on Ordinary Intervals?
  • 4 Arithmetic Operations on Fuzzy Intervals
  • 5 Conclusions
  • References
  • Analysis of Different Proposals to Improve the Dissemination of Information in University Digital Libraries
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 Basis of Recommender Systems
  • 2.2 Fuzzy Linguistic Approach
  • 3 Proposals to Improve the Dissemination of Information in Digital Libraries
  • 3.1 A Multi-disciplinar Recommender System to Advice Research Resources in University Digital Libraries
  • 3.2 Dealing with Incomplete Information in a Fuzzy Linguistic Recommender System to Disseminate Information in a University Digital Library
  • 3.3 An Improved Recommender System to Avoid the Persistent Information Overload in a University Digital Library
  • 3.4 A Quality Based Recommender System to Disseminate Information in a University Digital Library
  • 3.5 Comparative Analysis
  • 4 Conclusions and Future Work
  • References
  • Modeling Trends in the Hierarchical Fuzzy System for Multi-criteria Evaluation of Medical Data
  • 1 Introduction
  • 2 Clinical Scores to Evaluate
  • 3 Kosinski's Fuzzy Number Model
  • 4 Processing the Direction
  • 4.1 Inference Mechanism Based on the KFN Model
  • 5 Hierarchical Fuzzy Evaluator of HRQoL
  • 5.1 Evaluator - Low-Level Fuzzy Systems
  • 5.2 Evaluator - Fuzzy Sets for Output Fuzzy System
  • 6 Practical Results
  • 7 Summary and Future Actions
  • References
  • Using Fuzzy Sets in a Data-to-Text System for Business Service Intelligence
  • 1 Introduction
  • 2 Business Service Intelligence: The Obsidian Platform
  • 3 MonitorSI-Text: A D2T System Using Fuzzy Sets
  • 3.1 General Description
  • 3.2 Content Determination
  • 3.3 Text Realization
  • 4 Conclusions
  • References
  • An Approach to Fault Diagnosis Using Fuzzy Clustering Techniques
  • 1 Introduction
  • 2 Proposed Classification Methodology Using Fuzzy Clustering
  • 2.1 Fuzzy C-Means (FCM)
  • 2.2 Noise Clustering (NC)
  • 2.3 Kernel Fuzzy C-Means (KFCM)
  • 3 Study Case and Experimental Design
  • 4 Analysis of the Results
  • 4.1 Experiment 1
  • 4.2 Experiment 2
  • 4.3 Experiment 3
  • 4.4 Experiment 4
  • 5 Conclusions
  • References
  • Universal Generalized Net Model for Description of Metaheuristic Algorithms: Verification with the Bat Algorithm
  • 1 Introduction
  • 2 Bat Algorithm
  • 3 Generalized Net Model of the Bat Algorithm
  • 4 Bat Algorithm Described by the Universal Generalized Net
  • 5 Conclusion
  • References
  • Insurance Portfolio Containing a Catastrophe Bond and an External Help with Imprecise Level---A Numerical Analysis
  • 1 Introduction
  • 2 Risk Reserve Process and Its Generalization
  • 3 Optimization Goals
  • 4 Numerical Analysis
  • 4.1 Number of the Issued Cat Bonds
  • 4.2 Influence of the External Help
  • 5 Conclusions
  • References
  • Global Quality Measures for Fuzzy Association Rule Bases
  • 1 Introduction
  • 2 Preliminaries
  • 3 Statistical Characteristics of Rule Quality Measures
  • 4 Inference Driven Rule Base Measures
  • 5 Rule Base Measures Based on Singe Rule Validity
  • 6 Coverage-Based Measures
  • 7 Conclusion
  • References
  • Particle Swarm Optimization with Fuzzy Dynamic Parameters Adaptation for Modular Granular Neural Networks
  • Abstract
  • 1 Introduction
  • 2 Basic Concepts
  • 2.1 Modular Neural Networks
  • 2.2 Fuzzy Logic
  • 2.3 Granular Computing
  • 2.4 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 Non-optimized Results
  • 4.2 Optimized Results
  • 5 Conclusions
  • References
  • A Systematic Customer Oriented Approach based on Hesitant Fuzzy AHP for Performance Assessments of Service Departments
  • Abstract
  • 1 Introduction
  • 2 Hesitant Fuzzy AHP
  • 3 Application
  • 4 Conclusion
  • References
  • Edge Detection Based on Ordered Directionally Monotone Functions
  • 1 Introduction
  • 2 Preliminaries
  • 3 Ordered Directionally Monotone Functions
  • 4 Edge Detection Using OD Monotone Functions
  • 4.1 Step [ED2](ED2): Obtaining the Feature Image
  • 4.2 Fuzzy Measures
  • 4.3 Edge Detection Algorithm
  • 5 Conclusions
  • References
  • Adaptive Fuzzy Clustering of Multivariate Short Time Series with Unevenly Distributed Observations Based on Matrix Neuro-Fuzzy Self-organizing Network
  • 1 Introduction
  • 2 Fuzzy Probabilistic Clustering of Multivariate Short Time Series
  • 3 Sequential On-Line Clustering of Multivariate Time Series Based on Modified Neuro-Fuzzy Network by T. Kohonen
  • 4 Simulation
  • 5 Conclusion
  • References
  • Learning in Comparator Networks
  • 1 Introduction
  • 2 Related Work
  • 3 Comparator Networks
  • 4 Comparator Learning
  • 5 Case Study
  • 5.1 Results
  • 6 Summary
  • References
  • Fuzzy -pseudometrics and Fuzzy -pseudometric Spaces
  • 1 Introduction
  • 2 Fuzzy -pseudometrics and Fuzzy -pseudometric Spaces
  • 3 Topological Structure of a Fuzzy -pseudometric Space
  • 3.1 Supratopology m induced by a fuzzy -pseudometric m
  • 3.2 Topology m Induced by a Fuzzy -pseudometric m
  • 3.3 Subsets of a Fuzzy -pseudometric Spaces
  • 4 Sequences in Fuzzy -pseudometric Spaces
  • 4.1 Three Types of Convergence in Fuzzy -pseudometric Spaces
  • 4.2 Completeness of Fuzzy -pseudometric Spaces
  • 4.3 Fuzzy -pseudometric Version of a Baire Theorem
  • 4.4 Sequentiality Properties of Fuzzy -pseudometric Spaces
  • 5 Uniform Continuity for Mappings of Fuzzy -pseudometric Spaces
  • 6 Fuzzy Ultra -metric on the Set of Infinite Words
  • References
  • Generalized Net Modelling of the Intuitionistic Fuzzy Evaluation of the Quality Assurance in Universities
  • Abstract
  • 1 Introduction
  • 2 Proposed Assessment Model
  • 2.1 Determination of the Criterion Assessment
  • 2.2 Determination of the Final Assessment for the University
  • 3 Generalized Net Model
  • 4 Conclusion
  • Acknowledgments
  • References
  • How to Calibrate a Questionnaire for Risk Measurement?
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 Risk Aversion Coefficients
  • 2.2 Expected Utility
  • 2.3 Maximal Premium Model
  • 2.4 Power and Exponential Utility Functions
  • 3 Calibration of the Questionnaire and the Selected Utility Functions
  • 4 Maximal Premium
  • 5 Conclusions
  • References
  • Diagnostic Inference with the Dempster-Shafer Theory and a Fuzzy Input
  • 1 Introduction
  • 2 Methods
  • 3 Simulated Data
  • 4 Experiment
  • 5 Discussion and Conclusions
  • References
  • Analyzing Feedback Mechanisms in Group Decision Making Problems
  • 1 Introduction
  • 2 Preliminaries
  • 3 Description of the Feedback Mechanisms
  • 3.1 Basic Feedback Mechanism
  • 3.2 Adaptive Feedback Mechanism
  • 3.3 Feedback Mechanism Based on Experts' Importance
  • 4 Experimental Study
  • 5 Concluding Remarks
  • References
  • A Statistical Study for Quantifier-Guided Dominance and Non-Dominance Degrees for the Selection of Alternatives in Group Decision Making Problems
  • Abstract
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 The GDM Problem
  • 2.2 Selection Process
  • 3 Statistical Comparative Study: Experimental Design
  • 4 Statistical Comparative Study: Experimental Results
  • 4.1 Wilcoxon Signed-Rank Test: Experimental Results
  • 4.2 Descriptive Study: Experimental Results
  • 5 Conclusion
  • Acknowledgements
  • References
  • Using Bibliometrics and Fuzzy Linguistic Modeling to Deal with Cold Start in Recommender Systems for Digital Libraries
  • 1 Introduction
  • 2 Background
  • 2.1 Recommender Systems
  • 2.2 Cold Start Problem
  • 2.3 Fuzzy Linguistic Modeling
  • 3 Proposal Description
  • 3.1 System Concepts
  • 3.2 Information Representation
  • 3.3 Profiles Construction
  • 4 Experiments and Approach Evaluation
  • 5 Concluding Remarks
  • References
  • Type 2 Fuzzy Control Charts Using Likelihood and Deffuzzification Methods
  • Abstract
  • 1 Introduction
  • 2 Interval Type 2 Fuzzy Sets
  • 3 Comparison Methods for Type 2 Fuzzy Sets
  • 3.1 Chen and Lee's Likelihood Approach
  • 3.2 Kahraman et al.'s Defuzzification Approach
  • 4 Type 2 Fuzzy Control Charts
  • 5 Numerical Example
  • 6 Conclusions
  • References
  • Linked Open Data: Uncertainty in Equivalence of Properties
  • 1 Introduction
  • 2 Background
  • 2.1 Related Work
  • 2.2 Possibility Theory
  • 3 Property Equivalence Evaluation
  • 3.1 Concept
  • 3.2 Phase I: Direct Evaluation
  • 3.3 Phase II: Indirect Evaluation
  • 4 Case Study and Experiment
  • 4.1 Wikidata as Reference Source
  • 4.2 Property Matching: Wikidata-DBpedia
  • 4.3 Property Matching: Wikidata-YAGO
  • 4.4 Property Matching: Dbpedia-YAGO
  • 4.5 Visualization of Results
  • 4.6 Validation Experiment
  • 5 Conclusion
  • References
  • Power Means in Success Likelihood Index Method
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 SLIM
  • 2.2 Averaging Functions
  • 3 Generalized SLIM Case Study Application
  • 4 Generalized SLI Method for the Weighted Power Mean
  • 5 Conclusion
  • References
  • Three Dimensional Intercriteria Analysis over Intuitionistic Fuzzy Data
  • 1 Introduction
  • 2 Basic Definitions
  • 2.1 Short Notes on Intuitionistic Fuzzy Pairs
  • 2.2 Short Remarks on Index Matrices
  • 3 Three Dimensional Intercriteria Analysis Applied over Intuitionistic Fuzzy Data
  • 4 Conclusion
  • References
  • M-bornologies on L-valued Sets
  • 1 Introduction and Motivation
  • 1.1 Bornologies and Bornological Spaces
  • 1.2 L-bornologies or Bornologies on L-power-sets
  • 1.3 M-valued Bornologies on Powersets
  • 2 Prerequisites: The Context of the Work
  • 2.1 Lattices and Iccl-Monoids
  • 2.2 L-relations, L-valued Equalities and L-valued Sets
  • 3 M-bornologies on L-valued Sets
  • 3.1 LM-bornologies: Basic Definitions
  • 3.2 Lattice of LM-bornologies
  • 3.3 Decomposition of an LM Bornology into Level L-bornologies
  • 3.4 Construction of an M-bornology from a Family of L-bornologies on an L-valued Set
  • 4 Fuzzy Functions
  • 5 Category FBORN (L,M) of LM-bornological Spaces
  • 5.1 Bounded Fuzzy Functions of LM-bornological Spaces
  • 5.2 Preimages of LM-bornologies and Initial LM-bornologies Induced by Families of Sound Fuzzy Functions
  • 5.3 Images of LM-bornologies and Final LM-bornologies Induced by a Family of Fuzzy Functions
  • 5.4 Subcategories of the Category FSBORN(L, M)
  • References
  • Reduced IFAM Weight Matrix Representation Using Sparse Matrices
  • 1 Introduction and Motivation
  • 2 IFAM Evolution
  • 2.1 Implicative Fuzzy Associative Memory -- IFAM
  • 2.2 Reduced IFAM -- r-IFAM
  • 2.3 Binary IFAM -- b-IFAM
  • 3 Sparse Matrix Application
  • 4 Experiments
  • 5 Summary
  • References
  • A Note on Intuitionistic Fuzzy Modal-Like Operators Generated by Power Mean
  • 1 Introduction
  • 2 The Modal-Like Operators Generated by the Power Mean
  • 3 Conclusion
  • References
  • On Power Mean Generated Orderings Between Intuitionistic Fuzzy Pairs
  • 1 Introduction
  • 2 The Proposed Power Mean Orderings and Some Results
  • 3 Conclusion
  • References
  • Dynamical Behaviors of Fuzzy SIR Epidemic Model
  • 1 Introduction
  • 2 Proposed Fuzzy Model
  • 2.1 Analysis of the Fuzzy System
  • 3 Existence, Stability Analysis and Bifurcation of the Fuzzy Model
  • 3.1 Fuzzy Basic Reproduction Number
  • 3.2 Disease Control in Fuzzy Epidemic System
  • 4 Numerical Simulation
  • 5 Conclusion
  • References
  • Optimal Parameter Ranges in Fuzzy Inference Systems, Applied to Spatial Data
  • 1 Introduction
  • 2 Map Overlay Problem for Grids
  • 3 From Map Overlay to Rulebase
  • 3.1 Parameters
  • 3.2 Rules
  • 3.3 Spatial Aspects and Impact
  • 4 Customizing the Most Possible Ranges
  • 4.1 Local Most Possible Range
  • 4.2 Estimated Most Possible Range
  • 5 Conclusion
  • References
  • On Finite-Valued Bimodal Logics with an Application to Reasoning About Preferences
  • 1 Introduction
  • 2 The Minimal Bimodal Logic of a Finite Residuated Lattice
  • 2.1 Axiomatization
  • 3 Some Useful Axiomatic Extensions
  • 4 Modelling Fuzzy Preferences
  • 5 Conclusions
  • References
  • Improving Supervised Classification Algorithms by a Bipolar Knowledge Representation
  • 1 Introduction
  • 2 Bipolar Knowledge
  • 3 Probabilistic Bipolar Models in Supervised Classification Problems
  • 4 Experimental Framework
  • 4.1 Data Sets
  • 4.2 Algorithms Considered as Base Classifier
  • 4.3 Statistical Test for Performance Comparison
  • 5 Experimental Results
  • 6 Discussion and Final Remarks
  • References
  • Edge Detection Based on the Fusion of Multiscale Anisotropic Edge Strength Measurements
  • 1 Introduction
  • 2 Related Work
  • 3 Proposed Method
  • 4 Experimental Validation
  • 5 Conclusions
  • References
  • Fuzzy MCDA Without Defuzzification Based on Fuzzy Rank Acceptability Analysis
  • Abstract
  • 1 Introduction
  • 2 Preliminaries
  • 2.1 Fuzzy Numbers: Comparison and Ranking
  • 2.2 Yuan's Fuzzy Preference Relation
  • 2.3 Fuzzy Rank Acceptability Indices
  • 2.4 Fuzzy Rank Acceptability Analysis
  • 3 Fuzzy Multicriteria Acceptability Analysis
  • 3.1 FMCDA and the Overestimation Problem
  • 3.2 Implementation of FMAA in FMCDA
  • 4 Application of FMAVT-FMAA to a Case Study on Land-Use Planning
  • 5 Conclusions
  • References
  • A Portfolio of Minimum Risk in a Hybrid Uncertainty of a Possibilistic-Probabilistic Type: Comparative Study
  • 1 Introduction
  • 2 Necessary Concepts and Notations
  • 3 Expected Portfolio Return Under Conditions of Hybrid Uncertainty
  • 4 Portfolio Risk Assessment Under Conditions of Hybrid Uncertainty
  • 5 An Example of Minimum Risk Portfolio and Model Calculations
  • 6 Conclusion
  • References
  • Discrete Wavelet Transform and Fuzzy Logic Algorithm for Classification of Fault Type in Underground Cable
  • Abstract
  • 1 Introduction
  • 2 Simulations
  • 3 Decision Algorithm
  • 4 Conclusion
  • Acknowledgments
  • References
  • Investigation and Reduction of Effects of Transient Signals for Switching Capacitor into a Power System by Using an Experimental Test Set
  • Abstract
  • 1 Introduction
  • 2 Experimental Setup
  • 3 Experimental Results
  • 4 Conclusions
  • Acknowledgments
  • References
  • Practical Notes on Applying Generalised Stochastic Orderings to the Study of Performance of Classification Algorithms for Low Quality Data
  • 1 Introduction
  • 2 Basic Notions
  • 3 Application of Stochastic Orderings to Low Quality Data Classification Performance Evaluation
  • 3.1 Medical Data
  • 3.2 Expected Utility
  • 3.3 First Stochastic Dominance
  • 3.4 Statistical Preference Stochastic Dominance
  • 4 Proposed Approach
  • 4.1 Idea
  • 4.2 Definitions
  • 4.3 Evaluation
  • 5 Discussion and Further Work
  • References
  • Author Index

Dateiformat: PDF
Kopierschutz: Wasserzeichen-DRM (Digital Rights Management)

Systemvoraussetzungen:

  • Computer (Windows; MacOS X; Linux): Verwenden Sie zum Lesen die kostenlose Software Adobe Reader, Adobe Digital Editions oder einen anderen PDF-Viewer Ihrer Wahl (siehe E-Book Hilfe).
  • Tablet/Smartphone (Android; iOS): Installieren Sie bereits vor dem Download die kostenlose App Adobe Digital Editions oder die App PocketBook (siehe E-Book Hilfe).
  • E-Book-Reader: Bookeen, Kobo, Pocketbook, Sony, Tolino u.v.a.m. (nur bedingt: Kindle)

Das Dateiformat PDF zeigt auf jeder Hardware eine Buchseite stets identisch an. Daher ist eine PDF auch für ein komplexes Layout geeignet, wie es bei Lehr- und Fachbüchern verwendet wird (Bilder, Tabellen, Spalten, Fußnoten). Bei kleinen Displays von E-Readern oder Smartphones sind PDF leider eher nervig, weil zu viel Scrollen notwendig ist. Mit Wasserzeichen-DRM wird hier ein „weicher” Kopierschutz verwendet. Daher ist technisch zwar alles möglich – sogar eine unzulässige Weitergabe. Aber an sichtbaren und unsichtbaren Stellen wird der Käufer des E-Books als Wasserzeichen hinterlegt, sodass im Falle eines Missbrauchs die Spur zurückverfolgt werden kann.

Weitere Informationen finden Sie in unserer  E-Book Hilfe.