[HTML][HTML] AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …
components and functionalities required for analyzing and operating buildings. However, in …
Predictive models for concrete properties using machine learning and deep learning approaches: A review
Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
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 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 …
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 …
[HTML][HTML] Load forecasting techniques and their applications in smart grids
The growing success of smart grids (SGs) is driving increased interest in load forecasting
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
A review of data-driven approaches for prediction and classification of building energy consumption
A recent surge of interest in building energy consumption has generated a tremendous
amount of energy data, which boosts the data-driven algorithms for broad application …
amount of energy data, which boosts the data-driven algorithms for broad application …
Random Forest based hourly building energy prediction
Accurate building energy prediction plays an important role in improving the energy
efficiency of buildings. This paper proposes a homogeneous ensemble approach, ie, use of …
efficiency of buildings. This paper proposes a homogeneous ensemble approach, ie, use of …
[HTML][HTML] Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
Energy prediction models are used in buildings as a performance evaluation engine in
advanced control and optimisation, and in making informed decisions by facility managers …
advanced control and optimisation, and in making informed decisions by facility managers …
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 …