ArticleSensors (Basel, Switzerland)2021
An Attention-Based Multilayer GRU Model for Multistep-Ahead Short-Term Load Forecasting
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A multi-component hybrid model for renewable energy integrated grid power load forecasting: DWT, SAE, and FA-LSTM.Scientific reports · 2026Article
- Enhanced multi objective graph learning approach for optimizing traffic speed prediction on spatial and temporal features.Scientific reports · 2025Article
- Research on load forecasting based on CEEMDAN SE VMD and SelfAttention TCN fusion model.Scientific reports · 2025Article
- Prediction of Protein-Protein Interactions Based on Integrating Deep Learning and Feature Fusion.International journal of molecular sciences · 2024Article
- DDFC: deep learning approach for deep feature extraction and classification of brain tumors using magnetic resonance imaging in E-healthcare system.Scientific reports · 2024Article
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- High-Temperature Compression Behaviors and Constitutive Models of a 7046-Aluminum Alloy.Materials (Basel, Switzerland) · 2023Article
- Ultra-Short-Term Wind Power Forecasting Based on CGAN-CNN-LSTM Model Supported by Lidar.Sensors (Basel, Switzerland) · 2023Article
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- Energy consumption prediction using the GRU-MMattention-LightGBM model with features of Prophet decomposition.PloS one · 2023Article
- A hybrid model of modal decomposition and gated recurrent units for short-term load forecasting.PeerJ. Computer science · 2023Article
- Short-Term Drift Prediction of Multi-Functional Buoys in Inland Rivers Based on Deep Learning.Sensors (Basel, Switzerland) · 2022Article
- Multi-Step Hourly Power Consumption Forecasting in a Healthcare Building with Recurrent Neural Networks and Empirical Mode Decomposition.Sensors (Basel, Switzerland) · 2022Article
- Interpretable Short-Term Electrical Load Forecasting Scheme Using Cubist.Computational intelligence and neuroscience · 2022Article
- A Two-Stage Multistep-Ahead Electricity Load ForecastingScheme Based on LightGBM and Attention-BiLSTM.Sensors (Basel, Switzerland) · 2021Article
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4 authors.
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Abstract
Recently, multistep-ahead prediction has attracted much attention in electric load forecasting because it can deal with sudden changes in power consumption caused by various events such as fire and heat wave for a day from the present time. On the other hand, recurrent neural networks (RNNs), including long short-term memory and gated recurrent unit (GRU) networks, can reflect the previous point well to predict the current point. Due to this property, they have been widely used for multistep-ahead prediction. The GRU model is simple and easy to implement; however, its prediction performance is limited because it considers all input variables equally. 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 achieve significant performance improvements, especially when the input sequence of RNN is long. Through extensive experiments, we show that the proposed model outperforms other recent multistep-ahead prediction models in the building-level power consumption forecasting.
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