In this paper, we propose a short-term load forecasting model using an attention based GRU to focus more on the crucial variables.
Feb 26, 2021 · Through extensive experiments, we show that the proposed model outperforms other recent multistep-ahead prediction models in the building-level ...
In this paper, we propose a short-term load forecasting model using an attention based GRU to focus more on the crucial variables and demonstrate that this can ...
Feb 26, 2021 · The manuscript deals with a short term load forecasting based on recurrent neural network (LSTM). The manuscript follows standard approach to a ...
In this paper, we propose a short-term load forecasting model using an attention based GRU to focus more on the crucial variables and demonstrate that this can ...
Mar 1, 2021 · In this paper, we propose a short-term load forecasting model using an attention based GRU to focus more on the crucial variables and ...
An attention-based multilayer gru model for multistep-ahead short ...
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In this paper, we propose a short-term load forecasting model using an attention based GRU to focus more on the crucial variables and demonstrate that this can ...
CNN-GRU-Attention Based Short-Term Load Forecasting of ...
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To achieve accurate and efficient short-term load forecasting, an integral implementation framework is proposed based on convolutional neural network (CNN), ...
In this article, we propose a dual attention-based encoder–decoder framework, specifically designed to enhance multi-step ahead predictions in industrial ...
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