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Maier, Alexander: Identification of timed behavior models for diagnosis in production systems. 2015
Inhalt
Introduction
Motivation
Relevance to Related Work
Contribution of this Thesis
Realized and Potential Application Scenarios
Overview
Part I Foundations
The Core Issue: Modeling and Learning Time
Modeling Time - A Taxonomy
Learning Time - The Challenge
Conclusion
Formalisms
Basic notions
Automata Formalisms
Complexity of Identification of Finite Automata
The Identification Problem
Identification frameworks
Complexity of Identification of Finite Automata
Identification of Automata and Model-Based Anomaly Detection
Approaches for Anomaly Detection
Identification Algorithms for Finite Automata
Conclusion
Part II Algorithms and Theory
Algorithmic Results
Requirements on modeling formalism and identification algorithm
Bottom Up Timing Learning Algorithm (BUTLA)
Online Timed Automaton Learning Algorithm (OTALA)
Anomaly Detection
Adaptive Learning
Theoretical Results
Runtime Analysis of the Identification Algorithms
Evaluation of the Learning Error
Convergence and Identification In The Limit
Top-Down vs. Bottom-Up
Splitting vs. Non-Splitting
Online vs. Offline Identification
Runtime analysis of the anomaly detection algorithm
Empirical Results
Preliminaries
Runtime Analysis of the Identification Algorithms
Top-Down vs. Bottom-Up
Convergence of the Identification Algorithms
Empirical Analysis of the Anomaly Detection
BUTLA vs. OTALA
BUTLA vs. alternative methods
Part III Applications
Applications
Tool Box Implementation
Lemgo Model Factory
Plant at Jowat AG
Part IV Conclusion
Conclusions and Future Work
Conclusions
Future Work
List of Figures
List of Tables
Abbreviations
References
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