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Thesis Overview:

The development of a real-time power system stability assessment tool using decision trees and fuzzy logic is crucial in ensuring the reliability and efficiency of power systems. This thesis aims to address the challenges faced in assessing power system stability in real-time by utilizing advanced machine learning techniques such as decision trees and fuzzy logic.

Chapter One: Introduction
1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter Two: Literature Review
2.1 Overview of Power System Stability
2.2 Traditional Methods for Power System Stability Assessment
2.3 Machine Learning Techniques in Power System Stability Assessment
2.4 Decision Trees in Power System Stability Assessment
2.5 Fuzzy Logic in Power System Stability Assessment
2.6 Previous Studies on Real-Time Power System Stability Assessment
2.7 Challenges in Real-Time Power System Stability Assessment
2.8 Applications of Decision Trees and Fuzzy Logic in Power Systems
2.9 Advantages and Limitations of Decision Trees and Fuzzy Logic in Power Systems
2.10 Gaps in Existing Literature

Chapter Three: System Design and Methodology
3.1 Overview of the Proposed Real-Time Power System Stability Assessment Tool
3.2 Selection of Decision Trees and Fuzzy Logic as Machine Learning Techniques
3.3 Data Collection and Preprocessing
3.4 Feature Selection and Extraction
3.5 Decision Trees Construction
3.6 Fuzzy Logic Model Design
3.7 Integration of Decision Trees and Fuzzy Logic
3.8 Real-Time Implementation Considerations

Chapter Four: System Implementation
4.1 Development of the Real-Time Power System Stability Assessment Tool
4.2 Software and Hardware Requirements
4.3 Testing and Validation of the Tool
4.4 Performance Evaluation Metrics
4.5 Comparison with Traditional Methods
4.6 Case Studies and Results
4.7 Discussion on the Findings
4.8 Future Enhancements and Recommendations

Chapter Five: Conclusion and Summary
5.1 Recap of the Study Objectives
5.2 Summary of Findings
5.3 Contributions to the field of Power System Stability Assessment
5.4 Implications for Practice
5.5 Limitations and Future Research Directions
5.6 Final Thoughts and Recommendations

Overall, this thesis aims to contribute to the advancement of real-time power system stability assessment tools by leveraging decision trees and fuzzy logic. Through a comprehensive literature review, systematic system design and methodology, and thorough system implementation, this research will provide valuable insights and practical implications for the power industry.

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