[HTML][HTML] Interpretable machine learning for building energy management: A state-of-the-art review
Abstract Machine learning has been widely adopted for improving building energy efficiency
and flexibility in the past decade owing to the ever-increasing availability of massive building …
and flexibility in the past decade owing to the ever-increasing availability of massive building …
Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
[HTML][HTML] Review of urban building energy modeling (UBEM) approaches, methods and tools using qualitative and quantitative analysis
The world has witnessed a significant population shift to urban areas over the past few
decades. Urban areas account for about two-thirds of the world's total primary energy …
decades. Urban areas account for about two-thirds of the world's total primary energy …
State-of-the-art on research and applications of machine learning in the building life cycle
Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …
machine learning has been explored and applied to buildings research for the past decades …
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 …
Toward explainable artificial intelligence for regression models: A methodological perspective
In addition to the impressive predictive power of machine learning (ML) models, more
recently, explanation methods have emerged that enable an interpretation of complex …
recently, explanation methods have emerged that enable an interpretation of complex …
A review and reflection on open datasets of city-level building energy use and their applications
Data related to building energy use fuels the research and applications on building energy
efficiency, which is an essential measure to address global energy and environmental …
efficiency, which is an essential measure to address global energy and environmental …
Interpretable machine learning for predicting and evaluating hydrogen production via supercritical water gasification of biomass
S Zhao, J Li, C Chen, B Yan, J Tao, G Chen - Journal of Cleaner Production, 2021 - Elsevier
Supercritical water gasification (SCWG) of biomass for hydrogen production is a clean and
promising technology. However, due to many factors involved in SCWG process, including …
promising technology. However, due to many factors involved in SCWG process, including …
A novel improved model for building energy consumption prediction based on model integration
R Wang, S Lu, W Feng - Applied Energy, 2020 - Elsevier
Building energy consumption prediction plays an irreplaceable role in energy planning,
management, and conservation. Constantly improving the performance of prediction models …
management, and conservation. Constantly improving the performance of prediction models …
Investigating the performance of machine learning models combined with different feature selection methods to estimate the energy consumption of buildings
Abstract Machine learning is considered a promising method for developing building energy-
benchmarking models. However, the high dimensionality of building energy datasets can …
benchmarking models. However, the high dimensionality of building energy datasets can …