Systematic review of deep learning and machine learning for building energy
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 …
Modeling energy demand—a systematic literature review
PA Verwiebe, S Seim, S Burges, L Schulz… - Energies, 2021 - mdpi.com
In this article, a systematic literature review of 419 articles on energy demand modeling,
published between 2015 and 2020, is presented. This provides researchers with an …
published between 2015 and 2020, is presented. This provides researchers with an …
[HTML][HTML] Current status, challenges, and prospects of data-driven urban energy modeling: A review of machine learning methods
Urban energy modeling is essential in planning electricity generation and efficiently
managing electric power systems. Various urban energy models were developed for several …
managing electric power systems. Various urban energy models were developed for several …
Bridging the gap between complexity and interpretability of a data analytics-based process for benchmarking energy performance of buildings
Artificial intelligence (AI) is fast becoming a general purpose technology with outstanding
impacts in industries worldwide, thus supporting the Industry 4.0 revolution. In particular, the …
impacts in industries worldwide, thus supporting the Industry 4.0 revolution. In particular, the …
MATRYCS—A big data architecture for advanced services in the building domain
The building sector is undergoing a deep transformation to contribute to meeting the climate
neutrality goals set by policymakers worldwide. This process entails the transition towards …
neutrality goals set by policymakers worldwide. This process entails the transition towards …
A review of data-driven building performance analysis and design on big on-site building performance data
Building performance design (BPD) is a crucial pathway to achieve high-performance
buildings. Previous simulation-based BPD is being questioned due to the performance gaps …
buildings. Previous simulation-based BPD is being questioned due to the performance gaps …
[HTML][HTML] An interpretable data analytics-based energy benchmarking process for supporting retrofit decisions in large residential building stocks
Advanced energy benchmarking in residential buildings, using data-driven modeling,
provides a fast, accurate, and systematic approach to assessing energy performance and …
provides a fast, accurate, and systematic approach to assessing energy performance and …
Machine learning techniques focusing on the energy performance of buildings: a dimensions and methods analysis
The problem of energy consumption and the importance of improving existing buildings'
energy performance are notorious. This work aims to contribute to this improvement by …
energy performance are notorious. This work aims to contribute to this improvement by …
A data analytics-based energy information system (eis) tool to perform meter-level anomaly detection and diagnosis in buildings
Recently, the spread of smart metering infrastructures has enabled the easier collection of
building-related data. It has been proven that a proper analysis of such data can bring …
building-related data. It has been proven that a proper analysis of such data can bring …
Use of machine learning methods for indoor temperature forecasting
Improving the energy efficiency of the building sector has become an increasing concern in
the world, given the alarming reports of greenhouse gas emissions. The management of …
the world, given the alarming reports of greenhouse gas emissions. The management of …