Holland, Alexander: Transformation of graphical models to support knowledge transfer. 2008
Inhalt
- Contents
- Notation
- Acknowledgements
- Zusammenfassung
- 1. Introduction
- Part I. Basics and Methods
- 2. Knowledge Based Systems
- 3. Uncertainty Management
- 3.1. Introduction
- 3.2. Basic Definitions
- 3.3. Dempster-Shafer Theory of Evidence
- 3.4. Possibility Theory
- 3.5. Fuzzy Logic
- 3.6. Uncertainty Management Review
- Part II. Graphical Models
- 4. Bayesian Networks
- 4.1. Introduction
- 4.2. Inference in Bayesian Networks
- 4.3. Learning Bayesian Networks
- 4.4. Competing Fusion of Distributed Knowledge
- 4.5. Object-Oriented Bayesian Networks
- 4.6. Bayesian Networks Review
- 5. Decision Networks
- 5.1. Introduction
- 5.2. Sequential Decision Making
- 5.3. Modeling and Learning of Preferences
- 5.4. Information Gathering to Facilitate Reasonable Decision Making
- 5.5. Decision Networks Review
- Part III. Transformation Framework
- 6. Transformation of Graphical Models
- 6.1. Fuzzy Rule Bases
- 6.2. Transforming Decision Networks
- 6.3. Transformation as Optimization
- 6.4. Transformation Framework
- 6.5. Automatic Generation of a Rule Base by Means ofa Decision Network (AGoRuB)
- 6.6. Generalization on Fuzzy Rule Bases
- 6.7. Evaluation Measures
- 6.8. Transformation Process Flow
- 6.9. Transformation Review
- Part IV. Studies and Applications
- 7. Product Lifecycle Management
- 7.1. Basic Components of the PLM
- 7.2. Condition Monitoring
- 7.3. Adaptive Condition Monitoring for a RotationSpindle
- 7.4. Product Lifecycle Management Review
- Part V. Conclusions and Outlook
- 8. Conclusions
- 9. Outlook
- List of Figures
- List of Tables
- A. List of own Publications
- Bibliography
- Index