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This thesis presents an ARIMA-based LSTM model with an attention mechanism for load forecasting in smart grids. It includes a comprehensive literature review, research methodology, results, and discussions on the effectiveness of the proposed model. The research aims to enhance load forecasting accuracy, which is crucial for the efficient management of smart grids.

Author
rowaid ikram
Language
EN

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