[HTML][HTML] Advanced digital tools for data-informed and performance-driven design: a review of building energy consumption forecasting models based on machine …

AG Di Stefano, M Ruta, G Masera - Applied Sciences, 2023 - mdpi.com
Cities and buildings represent the core of human life, the nexus of economic activity, culture,
and growth. Although cities cover less than 10% of the global land area, they are notorious …

[HTML][HTML] Analyzing Long-Term and High Instantaneous Power Consumption of Buildings from Smart Meter Big Data with Deep Learning and Knowledge Graph …

RG Wang, WJ Ho, KC Chiang, YC Hung, JK Tai… - Energies, 2023 - mdpi.com
In the context of the growing emphasis on energy conservation and carbon reduction, the
widespread deployment of smart meters in residential and commercial buildings is …

Integrated Workflow Development for Data-Driven Neighborhood-Scale Building Performance Simulation

AG di Stefano, M Ruta… - ASME Journal of …, 2025 - asmedigitalcollection.asme.org
As urbanization intensifies, cities are key contributors to energy consumption and carbon
emissions, accounting for a significant portion of global energy use and CO 2 emissions …

Leveraging Machine Learning to Forecast Neighborhood Energy Use in Early Design Stages: A Preliminary Application

AG di Stefano, M Ruta, G Masera, S Hoque - Buildings, 2024 - re.public.polimi.it
The need for energy efficiency in neighborhood-scale architectural design is driven by
environmental imperatives and escalating energy costs. This study identifies three key …

[CITATION][C] Integrated Workflow Development for Data-Driven Neighborhood-Scale Building Performance Simulation

G Masera, S Hoque - 2024