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 …
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 …
Predicting residential energy consumption using CNN-LSTM neural networks
The rapid increase in human population and development in technology have sharply
raised power consumption in today's world. Since electricity is consumed simultaneously as …
raised power consumption in today's world. Since electricity is consumed simultaneously as …
[HTML][HTML] Multiobjective optimization of building energy consumption and thermal comfort based on integrated BIM framework with machine learning-NSGA II
Detailed parametric analysis and measurements are required to reduce building energy
usage while maintaining acceptable thermal conditions. This research suggested a system …
usage while maintaining acceptable thermal conditions. This research suggested a system …
A review of data-driven building energy consumption prediction studies
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 …
Deep learning framework to forecast electricity demand
The increasing world population and availability of energy hungry smart devices are major
reasons for alarmingly high electricity consumption in the current times. So far, various …
reasons for alarmingly high electricity consumption in the current times. So far, various …
Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques
Load forecasting problems have traditionally been addressed using various statistical
methods, among which autoregressive integrated moving average with exogenous inputs …
methods, among which autoregressive integrated moving average with exogenous inputs …
A review on time series forecasting techniques for building energy consumption
Energy consumption forecasting for buildings has immense value in energy efficiency and
sustainability research. Accurate energy forecasting models have numerous implications in …
sustainability research. Accurate energy forecasting models have numerous implications 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 …
Advanced data analytics for enhancing building performances: From data-driven to big data-driven approaches
Buildings have a significant impact on global sustainability. During the past decades, a wide
variety of studies have been conducted throughout the building lifecycle for improving the …
variety of studies have been conducted throughout the building lifecycle for improving the …