Leveraging Machine Learning to Predict Crop Yields for Sustainable Agriculture Development

1. Introduction 1.1 Background and Motivation 1.2 Objectives of the Study 1.3 Structure of the Thesis 2. Literature Review 2.1 Previous Studies on Crop Yields 2.2 Machine Learning in Agriculture 2.3 Sustainable Agriculture Practices 3. Methodology 3.1 Research Design 3.2 Data Collection Methods 3.3 Model Selection Criteria 4. Data Preparation 4.1 Data Cleaning Processes 4.2 Feature Selection Techniques 4.3 Data Normalization Methods 5. Machine Learning Models 5.1 Regression Models Overview 5.2 Neural Networks in Prediction 5.3 Ensemble Learning Methods 6. Implementation and Experiments 6.1 Model Training Procedures 6.2 Validation and Testing 6.3 Parameter Optimization 7. Results and Discussion 7.1 Prediction Accuracy Analysis 7.2 Comparison with Traditional Methods 7.3 Impact on Sustainable Practices 8. Conclusion and Future Work 8.1 Summary of Findings 8.2 Limitations of the Study 8.3 Recommendations for Future Research