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Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption—A systematic review
The building sector accounts for 36% of the total global energy usage and 40% of
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …
Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
The energy industry is at a crossroads. Digital technological developments have the
potential to change our energy supply, trade, and consumption dramatically. The new …
potential to change our energy supply, trade, and consumption dramatically. The new …
[HTML][HTML] Energy modelling and control of building heating and cooling systems with data-driven and hybrid models—A review
Implementing an efficient control strategy for heating, ventilation, and air conditioning
(HVAC) systems can lead to improvements in both energy efficiency and thermal …
(HVAC) systems can lead to improvements in both energy efficiency and thermal …
Energy 4.0: AI-enabled digital transformation for sustainable power networks
M Khalid - Computers & Industrial Engineering, 2024 - Elsevier
The considerable developments in green technology have changed several industries,
including the energy business and power sector. These advances have transformed power …
including the energy business and power sector. These advances have transformed power …
A deep learning framework for building energy consumption forecast
Increasing global building energy demand, with the related economic and environmental
impact, upsurges the need for the design of reliable energy demand forecast models. This …
impact, upsurges the need for the design of reliable energy demand forecast models. This …
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 …
AI-empowered methods for smart energy consumption: A review of load forecasting, anomaly detection and demand response
This comprehensive review paper aims to provide an in-depth analysis of the most recent
developments in the applications of artificial intelligence (AI) techniques, with an emphasis …
developments in the applications of artificial intelligence (AI) techniques, with an emphasis …
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 …
Prediction and optimization of energy consumption in an office building using artificial neural network and a genetic algorithm
The aim of this study is to propose a reliable method to optimize the energy consumption of
buildings. Also, the most effective input parameters are defined which are used in the energy …
buildings. Also, the most effective input parameters are defined which are used in the energy …
[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 …