Global ETD Search

A novel approach to determine building occupancy for cooling energy consumption prediction

Leung, MingCity, University of London2017

Building cooling load prediction is one of the key elements in the energy conservation achievements. Most of the mathematical models using in the industry nowadays include forward and inverse modeling approaches. However, these models consume much computer resources and require a longer …

city-london Repository record for A novel approach to determine building occupancy for cooling energy consumption prediction (opens in a new tab)

Short-term energy consumption prediction of heating, ventilation, and air conditioning (HVAC) systems using machine learning

Xu, Y.2025

tilburg Repository record for Short-term energy consumption prediction of heating, ventilation, and air conditioning (HVAC) systems using machine learning (opens in a new tab)

Prediction of peak energy demand and timestamping in commercial supermarkets using deep learning

Zhao, MengchenThe University of Western Ontario2023

Peak demand consumption is an ongoing research topic due to current environmental concerns. Accurate prediction of peak demand leads to improved power storage scheduling and smart grid management. However, existing researches on peak demand in commercial buildings lack focus on the timestamps for …

uwo Repository record for Prediction of peak energy demand and timestamping in commercial supermarkets using deep learning (opens in a new tab)

Machine learning for human-centered and value-sensitive building energy efficiency

Amasyali, KadirUniversity of Illinois at Urbana-Champaign2019

Enhancing building energy efficiency is one of the best strategies to reduce energy consumption and associated CO2 emissions. Recent studies emphasized the importance of occupant behavior as a key means of enhancing building energy efficiency. However, it is also critical that while we strive to …

uiuc Repository record for Machine learning for human-centered and value-sensitive building energy efficiency (opens in a new tab)

Adaptive sensing and personalized thermal comfort prediction for building energy efficiency

Bucarelli Sanchez, Nidia InesUniversity of Illinois at Urbana-Champaign2024

Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01

uiuc Repository record for Adaptive sensing and personalized thermal comfort prediction for building energy efficiency (opens in a new tab)

Exploratory Data Analysis (EDA) and Predictive Machine Learning (ML) for Buildings’ Energy Fault Detection

Nukala, Akshith

<p>Building energy load fault detection is a critical challenge in energy usage analysis. It helps uncover energy wastage, machinery/appliance degradation or inefficiency, and failures or faults in buildings’ HVAC (heating, ventilation, and air conditioning) systems. Early identification of …

columbus-state Repository record for Exploratory Data Analysis (EDA) and Predictive Machine Learning (ML) for Buildings’ Energy Fault Detection (opens in a new tab)

Influence of occupant's behaviour on indoor environmental quality and energy consumptions

FABI, VALENTINAPolitecnico di Torino2013

… sufficient to face great challenges of saving energy while still maintaining or even improving current comfort levels. Buildings are engineered using tested components and generally reliable systems whereas people can be unreliable, variable, and perhaps even irrational. The studies in …

poli-torino Repository record for Influence of occupant's behaviour on indoor environmental quality and energy consumptions (opens in a new tab)