Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit
about one-third of greenhouse gases. In the last few years, machine learning has achieved …
about one-third of greenhouse gases. In the last few years, machine learning has achieved …
Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics
In recent years deep neural networks have been proposed as a lightweight data-driven
model to capture high-dimensional, nonlinear physical processes to predict building thermal …
model to capture high-dimensional, nonlinear physical processes to predict building thermal …
Identifying grey-box thermal models with Bayesian neural networks
Smart thermostats are one of the most prevalent home automation products. Despite the
importance of having an accurate thermal model for the operation of smart thermostats …
importance of having an accurate thermal model for the operation of smart thermostats …
Efficacy of temporal and spatial abstraction for training accurate machine learning models: A case study in smart thermostats
Smart thermostats are increasingly popular in homes and buildings as they improve
occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills …
occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills …
Evaluation of data-driven thermal models for multi-hour predictions using residential smart thermostat data
Predictive residential HVAC controls can reduce a building's energy consumption; however,
they require customized thermal models for each home. In this setting, detailed physical …
they require customized thermal models for each home. In this setting, detailed physical …
PePTM: An Efficient and Accurate Personalized P2P Learning Algorithm for Home Thermal Modeling
Nowadays, the integration of home automation systems with smart thermostats is a common
trend, designed to enhance resident comfort and conserve energy. The introduction of smart …
trend, designed to enhance resident comfort and conserve energy. The introduction of smart …
Do auto-regressive models protect privacy? Inferring fine-grained energy consumption from aggregated model parameters
We investigate the extent to which statistical predictive models leak information about their
training data. More specifically, based on the use case of household (electrical) energy …
training data. More specifically, based on the use case of household (electrical) energy …
Efficient and Accurate Peer-to-Peer Training of Machine Learning Based Home Thermal Models
The integration of smart thermostats in home automation systems has created an opportunity
to optimize space heating and cooling through the use of machine learning, for example for …
to optimize space heating and cooling through the use of machine learning, for example for …
Data-driven identification of occupant-thermostat interactions in small commercial buildings
Small commercial buildings owners and utility managers often look for opportunities for
energy and greenhouse gas emission savings through various energy efficiency …
energy and greenhouse gas emission savings through various energy efficiency …
[PDF][PDF] Evaluation of model order reduction complexity for advanced control of commercial buildings
JAL Vilaplana - 2021 - researchgate.net
The buildings sector has experienced a drastic change during the last decades. The goals of
reducing energy consumption in buildings, while respecting the comfort of their occupants …
reducing energy consumption in buildings, while respecting the comfort of their occupants …