A review of machine learning in building load prediction
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …
opportunities for applying machine learning to building energy system modeling and …
Towards data-driven energy communities: A review of open-source datasets, models and tools
Energy communities will play a central role in the sustainable energy transition by hel**
inform and engage end users to become more responsible consumers of energy. However …
inform and engage end users to become more responsible consumers of energy. However …
[HTML][HTML] Quality of crowdsourced geospatial building information: A global assessment of OpenStreetMap attributes
F Biljecki, YS Chow, K Lee - Building and Environment, 2023 - Elsevier
Geospatial data of the building stock is essential in many domains pertaining to the built
environment. These datasets are often provided by governments, but crowdsourcing them …
environment. These datasets are often provided by governments, but crowdsourcing them …
A comparison of prediction and forecasting artificial intelligence models to estimate the future energy demand in a district heating system
Forecasting the short-term future energy demand in buildings and districts is a vital
component towards the optimization of energy use and consequently the reduction in …
component towards the optimization of energy use and consequently the reduction in …
Predictive maintenance in building facilities: A machine learning-based approach
The operation and maintenance of buildings has seen several advances in recent years.
Multiple information and communication technology (ICT) solutions have been introduced to …
Multiple information and communication technology (ICT) solutions have been introduced to …
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 …
Sadi: A self-adaptive decomposed interpretable framework for electric load forecasting under extreme events
Accurate prediction of electric load is crucial in power grid planning and management. In this
paper, we solve the electric load forecasting problem under extreme events such as …
paper, we solve the electric load forecasting problem under extreme events such as …
Federated learning-based short-term building energy consumption prediction method for solving the data silos problem
Transfer learning is an effective method to predict the energy consumption of information-
poor buildings by learning transferable knowledge from operational data of information-rich …
poor buildings by learning transferable knowledge from operational data of information-rich …
Predicting city-scale daily electricity consumption using data-driven models
Accurate electricity demand forecasts that account for impacts of extreme weather events are
needed to inform electric grid operation and utility resource planning, as well as to enhance …
needed to inform electric grid operation and utility resource planning, as well as to enhance …
Review of developments in whole-building statistical energy consumption models for commercial buildings
A significant portion of energy consumption occurs in buildings today. Accurate and easy-to-
implement methods are needed to calculate building energy consumption for a wide range …
implement methods are needed to calculate building energy consumption for a wide range …