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Automated Deep Learning for Load Forecasting
Accurate forecasting of electricity consumption is essential to ensure the performance and stability of the grid, especially as the use of renewable energy increases.
An algorithmic framework for the optimization of deep neural networks architectures and hyperparameters
Based on this search space we propose neighbourhood and evolution search operators to optimize both the architecture and hyper-parameters of our networks.
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