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Long Short Term Memory and Rolling Window Technique for Modeling Power Demand Prediction

Publisher : Proceedings of the 2nd International Conference on Intelligent Computing and Control Systems, ICICCS 2018

Year : 2019

Abstract : Forecasting monthly electric energy consumption is significant for electric power engineering and its production planning. This paper has implemented Long Short Term Memory (LSTM) technique to forecast the energy consumption of a University and further it proposes a model to automate the forecast. The paper also highlights the improvement in performance with the implementation of rolling window technique over LSTM. © 2018 IEEE.

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