Modeling and forecasting building energy consumption: A review of data-driven techniques
Building energy consumption modeling and forecasting is essential to address buildings
energy efficiency problems and take up current challenges of human comfort, urbanization …
energy efficiency problems and take up current challenges of human comfort, urbanization …
[HTML][HTML] A review of data mining technologies in building energy systems: Load prediction, pattern identification, fault detection and diagnosis
With the advent of the era of big data, buildings have become not only energy-intensive but
also data-intensive. Data mining technologies have been widely utilized to release the …
also data-intensive. Data mining technologies have been widely utilized to release the …
A novel CNN-GRU-based hybrid approach for short-term residential load forecasting
Electric energy forecasting domain attracts researchers due to its key role in saving energy
resources, where mainstream existing models are based on Gradient Boosting Regression …
resources, where mainstream existing models are based on Gradient Boosting Regression …
A hybrid model for building energy consumption forecasting using long short term memory networks
Data driven building energy consumption forecasting models play a significant role in
enhancing the energy efficiency of the buildings through building energy management …
enhancing the energy efficiency of the buildings through building energy management …
A comprehensive review of machine learning and IoT solutions for demand side energy management, conservation, and resilient operation
The energy consumption of major equipment in residential and industrial facilities can be
minimized through a variety of cost-effective energy-saving measures. Most saving …
minimized through a variety of cost-effective energy-saving measures. Most saving …
[HTML][HTML] Prediction of home energy consumption based on gradient boosting regression tree
Energy consumption prediction of buildings has drawn attention in the related literature
since it is very complex and affected by various factors. Hence, a challenging work is …
since it is very complex and affected by various factors. Hence, a challenging work is …
A survey on home energy management
Energy is a vital resource for human activities and lifestyle, powering important everyday
infrastructures and services. Currently, pollutant and non-renewable sources, such as fossil …
infrastructures and services. Currently, pollutant and non-renewable sources, such as fossil …
Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles
Implementing machine-learning models in real applications is crucial to achieving intelligent
building control and high energy efficiency. Over the past few decades, numerous studies …
building control and high energy efficiency. Over the past few decades, numerous studies …
Towards efficient electricity forecasting in residential and commercial buildings: A novel hybrid CNN with a LSTM-AE based framework
Due to industrialization and the rising demand for energy, global energy consumption has
been rapidly increasing. Recent studies show that the biggest portion of energy is consumed …
been rapidly increasing. Recent studies show that the biggest portion of energy is consumed …
Building energy consumption prediction: An extreme deep learning approach
Building energy consumption prediction plays an important role in improving the energy
utilization rate through hel** building managers to make better decisions. However, as a …
utilization rate through hel** building managers to make better decisions. However, as a …