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September 18, 2025

Evaluating Neural Network-Based Energy Forecasting With Mixed Variables and Limited Data

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Deep neural networks effectively forecast electricity demand, significantly outperforming statistical methods.
The LSTM model shows superior performance, especially for forecasting periods of 7 to 30 days.
Analysis utilized multivariate time series data, incorporating meteorological and time-related variables.
The study highlights the importance of historical data for training effective forecasting models across different horizons.

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This analysis evaluates deep neural networks and statistical methods for predicting electricity demand, suggesting efficiency in energy management.

Lugmania et al. (2025) studied this question.

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This analysis evaluates deep neural networks and statistical methods for predicting electricity demand, suggesting efficiency in energy management.