A review of data-driven building energy consumption prediction studies
K Amasyali, NM El-Gohary - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy is the lifeblood of modern societies. In the past decades, the world's energy
consumption and associated CO 2 emissions increased rapidly due to the increases in …
consumption and associated CO 2 emissions increased rapidly due to the increases in …
Machine learning for estimation of building energy consumption and performance: a review
Ever growing population and progressive municipal business demands for constructing new
buildings are known as the foremost contributor to greenhouse gasses. Therefore …
buildings are known as the foremost contributor to greenhouse gasses. Therefore …
Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters
The industrial sector consumes about one-third of global energy, making them a frequent
target for energy use reduction. Variation in energy usage is observed with weather …
target for energy use reduction. Variation in energy usage is observed with weather …
Forecasting energy use in buildings using artificial neural networks: A review
J Runge, R Zmeureanu - Energies, 2019 - mdpi.com
During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …
have increased drastically due to a wide variety of factors including both technological and …
Systematic review of deep learning and machine learning for building energy
S Ardabili, L Abdolalizadeh, C Mako, B Torok… - Frontiers in Energy …, 2022 - frontiersin.org
The building energy (BE) management plays an essential role in urban sustainability and
smart cities. Recently, the novel data science and data-driven technologies have shown …
smart cities. Recently, the novel data science and data-driven technologies have shown …
Energy consumption forecasting based on Elman neural networks with evolutive optimization
Buildings are an essential part of our social life. People spend a substantial fraction of their
time and spend a high amount of energy in them. There is a grand variety of systems and …
time and spend a high amount of energy in them. There is a grand variety of systems and …
A scoping review of deep neural networks for electric load forecasting
The increasing dependency on electricity and demand for renewable energy sources means
that distributed system operators face new challenges in their grid. Accurate forecasts of …
that distributed system operators face new challenges in their grid. Accurate forecasts of …
Application of neural networks for evaluating energy performance certificates of residential buildings
F Khayatian, L Sarto - Energy and Buildings, 2016 - Elsevier
Abstract The Energy Performance Building Directive 91 of 2002, mandates Member States
of the European Union to enforce energy certification of buildings through local legislation …
of the European Union to enforce energy certification of buildings through local legislation …
A short-term energy prediction system based on edge computing for smart city
The development of Internet of Things technologies has provided potential for real-time
monitoring and control of environment in smart cities. In the field of energy management …
monitoring and control of environment in smart cities. In the field of energy management …
Forecasting building energy consumption with deep learning: A sequence to sequence approach
L Sehovac, C Nesen, K Grolinger - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Energy Consumption has been continuously increasing due to the rapid expansion of high-
density cities, and growth in the industrial and commercial sectors. To reduce the negative …
density cities, and growth in the industrial and commercial sectors. To reduce the negative …