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 …
Machine learning applications in urban building energy performance forecasting: A systematic review
In developed countries, buildings are involved in almost 50% of total energy use and 30% of
global green-house gas emissions. Buildings' operational energy is highly dependent on …
global green-house gas emissions. Buildings' operational energy is highly dependent on …
Building energy consumption prediction for residential buildings using deep learning and other machine learning techniques
The high proportion of energy consumed in buildings has engendered the manifestation of
many environmental problems which deploy adverse impacts on the existence of mankind …
many environmental problems which deploy adverse impacts on the existence of mankind …
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 …
Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm
XJ Luo, LO Oyedele - Advanced Engineering Informatics, 2021 - Elsevier
The real-world building can be regarded as a comprehensive energy engineering system;
its actual energy consumption depends on complex affecting factors, including various …
its actual energy consumption depends on complex affecting factors, including various …
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 …
Conventional models and artificial intelligence-based models for energy consumption forecasting: A review
Conventional models and artificial intelligence (AI)-based models have been widely applied
for energy consumption forecasting over the past decades. This paper reviews conventional …
for energy consumption forecasting over the past decades. This paper reviews conventional …
Statistical investigations of transfer learning-based methodology for short-term building energy predictions
The wide availability of massive building operational data has motivated the development of
advanced data-driven methods for building energy predictions. Existing data-driven …
advanced data-driven methods for building energy predictions. Existing data-driven …
Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings
Accurate forecast of energy consumption is essential in building energy management.
Owing to the variation of outdoor weather condition among different seasons, year-round …
Owing to the variation of outdoor weather condition among different seasons, year-round …
DB-Net: A novel dilated CNN based multi-step forecasting model for power consumption in integrated local energy systems
In the era of cutting edge technology, excessive demand for electricity is rising day by day,
due to the exponential growth of population, electricity reliant vehicles, and home …
due to the exponential growth of population, electricity reliant vehicles, and home …