Spatio-temporal prediction of total energy consumption in multiple regions using explainable deep neural network
S Peng, L Fan, L Zhang, H Su, Y He, Q He, X Wang… - Energy, 2024 - Elsevier
Energy consumption forecasting is essential for energy system integration and
management. However, existing studies mainly focus on temporal features of energy …
management. However, existing studies mainly focus on temporal features of energy …
A deep learning framework using multi-feature fusion recurrent neural networks for energy consumption forecasting
L Fang, B He - Applied Energy, 2023 - Elsevier
Accurate energy load forecasting can not only provide favorable conditions for ensuring
energy security but also reduce carbon emissions and thereby slow down the process of …
energy security but also reduce carbon emissions and thereby slow down the process of …
[HTML][HTML] Time series forecasting with multi-headed attention-based deep learning for residential energy consumption
Predicting residential energy consumption is tantamount to forecasting a multivariate time
series. A specific window for several sensor signals can induce various features extracted to …
series. A specific window for several sensor signals can induce various features extracted to …
A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models
For energy suppliers, forecasting the energy demand with accuracy is essential. The current
studies in the literature have employed various statistical and machine/deep learning …
studies in the literature have employed various statistical and machine/deep learning …
Short-term energy forecasting framework using an ensemble deep learning approach
M Ishaq, S Kwon - IEEE Access, 2021 - ieeexplore.ieee.org
Industrial and building sectors demand efficient smart energy strategies, techniques of
optimization, and efficient management for reducing global energy consumption due to the …
optimization, and efficient management for reducing global energy consumption due to the …
[HTML][HTML] Short-mid term electricity consumption prediction using non-intrusive attention-augmented deep learning model
Estimates of electricity consumption (EC) can provide effective guidance for energy
allocation and energy-saving measures. For improving the accuracy of short-mid term EC …
allocation and energy-saving measures. For improving the accuracy of short-mid term EC …
[HTML][HTML] Accurate deep model for electricity consumption forecasting using multi-channel and multi-scale feature fusion CNN–LSTM
X Shao, CS Kim, P Sontakke - Energies, 2020 - mdpi.com
Electricity consumption forecasting is a vital task for smart grid building regarding the supply
and demand of electric power. Many pieces of research focused on the factors of weather …
and demand of electric power. Many pieces of research focused on the factors of weather …
A deep learning neural network for the residential energy consumption prediction
J Huang, C Pang, W Yang, X Zeng… - IEEJ Transactions on …, 2022 - Wiley Online Library
In order to provide guidance for demand‐side management and improve energy efficiency,
the accuracy of residential electricity demand forecasting plays a significant role. Data …
the accuracy of residential electricity demand forecasting plays a significant role. Data …
Stacking Deep learning and Machine learning models for short-term energy consumption forecasting
S Reddy, S Akashdeep, R Harshvardhan… - Advanced Engineering …, 2022 - Elsevier
Accurate prediction of electricity consumption is essential for providing actionable insights to
decision-makers for managing volume and potential trends in future energy consumption for …
decision-makers for managing volume and potential trends in future energy consumption for …
[HTML][HTML] Dual-stage attention-based long-short-term memory neural networks for energy demand prediction
Forecasting energy demand of residential buildings plays an important role in the operation
of smart cities, as it forms the basis for decision-making in the planning and operation of …
of smart cities, as it forms the basis for decision-making in the planning and operation of …