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IEEE/ICACT20250070 Slide.24        [Big Slide]	Oral Presentation
	Conclusion This paper presented a decentralized architecture for privacy-preserving electricity load forecasting across smart power grids. We customize a layered federated learning approach to arrange an integrated predictive model between distributed grid components. Proposed federated model achieves 98.60 % accuracy and 1.4% miss-rate. Proposed Federated Learning Approach gives more accurate results as compared to previous published approaches like GA, ANN etc.

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