Chapter ONE

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 Research
1.9 Definition of Terms

Chapter TWO

2.1 Overview of Short-term Electric Power Forecasting
2.2 Artificial Neural Networks (ANN) in Power Forecasting
2.3 Literature Review on Short-term Power Forecasting Models
2.4 Case Studies on Power Forecasting Using ANN
2.5 Challenges in Short-term Power Forecasting
2.6 Advantages of Artificial Neural Networks in Power Forecasting
2.7 Comparison with Traditional Forecasting Methods
2.8 Impact of Data Quality on Forecasting Accuracy
2.9 Future Trends in Short-term Power Forecasting
2.10 Summary of Literature Review

Chapter THREE

3.1 Research Methodology Overview
3.2 Research Design and Rationale
3.3 Data Collection Methods
3.4 Data Analysis Techniques
3.5 Model Development Approach
3.6 Validation and Testing Procedures
3.7 Ethical Considerations
3.8 Limitations of Methodology

Chapter FOUR

4.1 Data Analysis and Results Interpretation
4.2 Performance Evaluation Metrics
4.3 Comparison of Forecasting Models
4.4 Impact of Input Variables on Forecast Accuracy
4.5 Discussion on Forecasting Errors
4.6 Sensitivity Analysis of the ANN Model
4.7 Case Studies and Application Scenarios
4.8 Managerial Implications of Forecasting Findings

Chapter FIVE

5.1 Summary of Findings
5.2 Conclusion and Recommendations
5.3 Contributions to Knowledge
5.4 Implications for Future Research
5.5 Practical Applications of Research Findings