Principles, research status, and prospects of feature engineering for data-driven building energy prediction: A comprehensive review
With the rapid growth in the volume of relevant and available data, feature engineering is
emerging as a popular research subject in data-driven building energy prediction owing to …
emerging as a popular research subject in data-driven building energy prediction owing to …
Data-driven estimation of building energy consumption and GHG emissions using explainable artificial intelligence
Energy consumption prediction is an integral part of planning and controlling energy used in
the building sector which accounts for 40% of the global energy consumption and a …
the building sector which accounts for 40% of the global energy consumption and a …
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 …
PSO-Stacking improved ensemble model for campus building energy consumption forecasting based on priority feature selection
Building energy consumption forecasting plays an indispensable role in energy resource
management and scheduling. When using an ensemble forecasting model, it is difficult to …
management and scheduling. When using an ensemble forecasting model, it is difficult to …
Space cooling energy usage prediction based on utility data for residential buildings using machine learning methods
Y Feng, Q Duan, X Chen, SS Yakkali, J Wang - Applied energy, 2021 - Elsevier
The energy used for space cooling in residential buildings has a significant influence on
household energy performance. This study aims to develop a user-friendly, infrastructure …
household energy performance. This study aims to develop a user-friendly, infrastructure …
Techno-financial evaluation of a hybrid renewable solution for supplying the predicted power outages by machine learning methods in rural areas
From a worldwide perspective, increasing grid reliability by applying renewable energies is
one of the most affordable and environmentally-friendly options available for governments …
one of the most affordable and environmentally-friendly options available for governments …
Comparative analysis on predictability of natural ventilation rate based on machine learning algorithms
The demand for efficient natural ventilation (NV) systems has increased for the development
of sustainable buildings. However, the uncertainty of NV remains a challenging issue for …
of sustainable buildings. However, the uncertainty of NV remains a challenging issue for …
Comparison of machine-learning models for predicting short-term building heating load using operational parameters
Y Zhou, Y Liu, D Wang, X Liu - Energy and Buildings, 2021 - Elsevier
Short-term building energy consumption prediction is of great significance to the optimal
operation of building energy systems and conservation. Machine-learning models are …
operation of building energy systems and conservation. Machine-learning models are …
Hybrid framework combining grey system model with Gaussian process and STL for CO2 emissions forecasting in developed countries
Accurate forecasting of carbon dioxide (CO 2) emissions is crucial for achieving carbon
neutrality early, as CO 2 is the primary component of greenhouse gases. The time series of …
neutrality early, as CO 2 is the primary component of greenhouse gases. The time series of …
Smart peer-to-peer and transactive energy sharing architecture considering incentive-based demand response programming under joint uncertainty and line outage …
Due to the widespread deployment of distributed energy resources, renewable energies and
battery energy storage, the peer to peer (P2P) energy trading schematic has gained the …
battery energy storage, the peer to peer (P2P) energy trading schematic has gained the …