[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 …
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 …
Exploring complex water stress–gross primary production relationships: Impact of climatic drivers, main effects, and interactive effects
The dominance of vapor pressure deficit (VPD) and soil water content (SWC) for plant water
stress is still under debate. These two variables are strongly coupled and influenced by …
stress is still under debate. These two variables are strongly coupled and influenced by …
Temporal variations of carbon and water fluxes in a subtropical mangrove forest: Insights from a decade-long eddy covariance measurement
Mangroves, highly efficient ecosystems in sequestering CO 2, are strongly impacted by
climate change. The lack of long-term observation in mangroves hinders the evaluation of …
climate change. The lack of long-term observation in mangroves hinders the evaluation of …
Guidance for good practice in the application of machine learning in development of toxicological quantitative structure-activity relationships (QSARs)
SJ Belfield, MTD Cronin, SJ Enoch, JW Firman - PloS one, 2023 - journals.plos.org
Recent years have seen a substantial growth in the adoption of machine learning
approaches for the purposes of quantitative structure-activity relationship (QSAR) …
approaches for the purposes of quantitative structure-activity relationship (QSAR) …
[HTML][HTML] Uncovering the financial impact of energy-efficient building characteristics with eXplainable artificial intelligence
K Konhäuser, T Werner - Applied Energy, 2024 - Elsevier
The urgency to combat climate change through decarbonization efforts is more crucial than
ever. The global building sector is one of the primary contributors to carbon emissions, yet …
ever. The global building sector is one of the primary contributors to carbon emissions, yet …
Atmospheric water demand constrains net ecosystem production in subtropical mangrove forests
Subtropical mangroves have great potential to sequester atmospheric carbon dioxide (CO 2)
and thus significantly contribute to climate change mitigation. Meanwhile, the carbon cycling …
and thus significantly contribute to climate change mitigation. Meanwhile, the carbon cycling …
[HTML][HTML] Prediction and mechanism explain of austenite-grain growth during reheating of alloy steel using XAI
Austenite-grain growth is an important factor in heat treatments, such as annealing and
normalizing, for controlling the microstructures and overall properties of alloy steels. Thus …
normalizing, for controlling the microstructures and overall properties of alloy steels. Thus …
State of the art in applications of machine learning in steelmaking process modeling
R Zhang, J Yang - International Journal of Minerals, Metallurgy and …, 2023 - Springer
With the development of automation and informatization in the steelmaking industry, the
human brain gradually fails to cope with an increasing amount of data generated during the …
human brain gradually fails to cope with an increasing amount of data generated during the …
A wavelet feature-based neural network approach to estimate electrical arc characteristics
M Farzanehdehkordi, S Ghaffaripour, K Tirdad… - Electric Power Systems …, 2022 - Elsevier
Abstract Electric Arc Furnaces (EAFs) account for almost half of the North American steel
production. Arc furnaces draw high and dynamic electrical power to melt scrap metal loads …
production. Arc furnaces draw high and dynamic electrical power to melt scrap metal loads …