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The aim is to develop a machine learning framework that accurately predicts CO₂ emissions using historical data.

April 8, 2026Open Access

Machine Learning–Based Framework For Accurate CO₂ Emission Prediction And Environmental Impact Analysis

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The aim is to develop a machine learning framework that accurately predicts CO₂ emissions using historical data.
Implemented various regression algorithms including Linear Regression and SMOreg
Utilized historical environmental and fuel consumption data for analysis
Conducted data preprocessing including cleaning and normalization
Evaluated model performance using metrics like MAE and RMSE
Machine learning models effectively predicted CO₂ emissions
SMOreg outperformed other models in accuracy and error reduction
The framework supports understanding emission trends for better decision-making

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Demonstrates improved CO₂ emission predictions in environmental data using machine learning techniques, suggesting better policy support.

P.Reddi et al. (2026) studied this question.

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Demonstrates improved CO₂ emission predictions in environmental data using machine learning techniques, suggesting better policy support.