Interactive GUI for CO₂ Emissions Analysis and AI-Based Fore

This GUI enables users to interactively analyze historical CO₂ emissions data by country and sector, perform basic statistical analysis.

Key Features:

✔ Interactive GUI with dropdown selection for country and sector

✔ Automatic statistical analysis (Mean, Std Dev, Min, Max)

✔ Forecasting using Linear Regression, Decision Tree, Neural Network

✔ Visual display of historical and forecasted CO₂ emissions

✔ Comparative performance metrics (MAE, MSE, RMSE, R²)

✔ Clean command window and figure management on every run

Instructions to Execute:

1. Place your dataset.csv file containing CO₂ emissions data in the same folder as the .m file.The dataset must contain columns:

• country (string)
• sector (string)
• date (format: dd/MM/yyyy)
• value (numeric, CO₂ emissions)

1. Open the .m file in MATLAB.
2. Run the script. The GUI window will appear centered on the screen.
3. From the dropdown menus, select a country and sector.
4. Click Run Analysis.

• The GUI will display statistical results.
• Historical and forecasted CO₂ emissions plots will open.
• Forecast results and performance metrics will be printed in the Command Window.

1. To analyze a different country or sector, simply change the selection and click Run Analysis again.

Requirements:

✔ MATLAB R2021b or newer recommended

✔ Statistics and Machine Learning Toolbox