Deep learning for time series forecasting: Advances and open problems
A time series is a sequence of time-ordered data, and it is generally used to describe how a
phenomenon evolves over time. Time series forecasting, estimating future values of time …
phenomenon evolves over time. Time series forecasting, estimating future values of time …
Deep learning for variable renewable energy: a systematic review
J Klaiber, C Van Dinther - ACM Computing Surveys, 2023 - dl.acm.org
In recent years, both fields, AI and VRE, have received increasing attention in scientific
research. Thus, this article's purpose is to investigate the potential of DL-based applications …
research. Thus, this article's purpose is to investigate the potential of DL-based applications …
A survey on deep learning for time-series forecasting
A Mahmoud, A Mohammed - Machine learning and big data analytics …, 2021 - Springer
Deep learning, one of the most remarkable techniques of machine learning, has been a
major success in many fields, including image processing, speech recognition, and text …
major success in many fields, including image processing, speech recognition, and text …
Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature
The ever-changing data science landscape is fueling innovation in the built environment
context by providing new and more effective means of converting large raw data sets into …
context by providing new and more effective means of converting large raw data sets into …
Advances in deep learning techniques for short-term energy load forecasting applications: A review
R Chandrasekaran, SK Paramasivan - Archives of Computational Methods …, 2024 - Springer
Today, the majority of the leading power companies place a significant emphasis on
forecasting the electricity load in the balance of power and administration. Meanwhile, since …
forecasting the electricity load in the balance of power and administration. Meanwhile, since …
A novel approach for short-term energy forecasting in smart buildings
M Jayashankara, P Shah, A Sharma… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Efficient energy management is required for optimal energy consumption. The building
sector consumes 40% of the total global energy production and is expected to reach 50% by …
sector consumes 40% of the total global energy production and is expected to reach 50% by …
Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis
Research is needed to explore the limitations and potential for improvement of machine
learning for building energy prediction. With this aim, the ASHRAE Great Energy Predictor III …
learning for building energy prediction. With this aim, the ASHRAE Great Energy Predictor III …
A review of energy consumption forecasting in smart buildings: Methods, input variables, forecasting horizon and metrics
D Mariano-Hernández, L Hernández-Callejo… - Applied Sciences, 2020 - mdpi.com
Buildings are among the largest energy consumers in the world. As new technologies have
been developed, great advances have been made in buildings, turning conventional …
been developed, great advances have been made in buildings, turning conventional …
A survey on deep learning for building load forecasting
I Patsakos, E Vrochidou… - … Problems in Engineering, 2022 - Wiley Online Library
Energy consumption forecasting is essential for efficient resource management related to
both economic and environmental benefits. Forecasting can be implemented through …
both economic and environmental benefits. Forecasting can be implemented through …
Conditional wasserstein gan for energy load forecasting in large buildings
GS Năstăsescu, DC Cercel - 2022 International Joint …, 2022 - ieeexplore.ieee.org
Energy forecasting is necessary for planning electricity consumption, and large buildings
play a huge role when making these predictions. Because of its importance, numerous …
play a huge role when making these predictions. Because of its importance, numerous …