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Recurrent Neural Networks Application to Forecasting with Two Cases: Load and Pollution

... increase of training data, deep learning has been widely applied in the field of forecasting. This paper focuses on the analysis of the application of recurrent neural networks (RNN), an advanced algorithm in deep learning, in the forecasting task. The forecasting models based on long short-term memory (LSTM) and gated recurrent unit (GRU) were established respectively, and the real data of power load and air pollution were verified. Compared with traditional machine learning algorithms, the simulation ...

Теги: deep learning , forecasting , gru , lstm , decision making , intelligent computing , learning algorithms , machine learning , pollution , forecasting modeling , forecasting models , forecasting problems , neural netwo


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