Federated Learning on Smart Meter Dataset for load forecasting using clustering and light weight FNN
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Updated
Nov 1, 2023 - Jupyter Notebook
Federated Learning on Smart Meter Dataset for load forecasting using clustering and light weight FNN
The code and dataset used in the published paper: Smart grid stability prediction using Adaptive Aquila Optimizer and ensemble stacked BiLSTM
Labeled GOOSE traffic datasets for evaluating intrusion detection against spoofing attacks in IEC 61850 substations.
This project builds a self-learning, hybrid IoT architecture that connects every household node and transformer to a central intelligence layer — providing real-time visibility, load balancing, and automated control across both urban and rural grids.
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