AINeutralarXiv – CS AI · 10h ago6/10
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Federated Learning for Global Carbon Emission Forecasting: A Hybrid Time-Series Approach with Statistical and Neural Models
Researchers propose a federated learning framework that combines ARIMA, GARCH, LSTM-Attention, and XGBoost models to forecast global carbon emissions while preserving data privacy. The system enables collaborative forecasting across distributed clients without sharing raw data, achieving R² values averaging 0.73 across 14 test clients.