More Buildings Make More Generalizable Models—Benchmarking Prediction Methods on Open Electrical Meter Data

由 Miller, Clayton
出版 2022

What's in the box?! Towards explainable machine learning applied to non-residential building smart meter classification

由 Miller, Clayton
出版 2019

The Building Data Genome Project: An open, public data set from non-residential building electrical meters

由 Miller, Clayton, Meggers, Forrest
出版 2021

Mining electrical meter data to predict principal building use, performance class, and operations strategy for hundreds of non-residential buildings

由 Miller, Clayton, Meggers, Forrest
出版 2021

Poster Abstract: Towards Class-Balancing Human Comfort Datasets with GANs

由 Quintana, Matias, Miller, Clayton
出版 2021

Using Google Trends as a proxy for occupant behavior to predict building

由 Fu, Chun, Miller, Clayton
出版 2022

BEEM: Data-driven building energy benchmarking for Singapore

由 Arjunan, Pandarasamy, Poolla, Kameshwar, Miller, Clayton
出版 2022

EnergyStar plus plus : Towards more accurate and explanatory building energy benchmarking

由 Arjunan, Pandarasamy, Poolla, Kameshwar, Miller, Clayton
出版 2021

A review of unsupervised statistical learning and visual analytics techniques applied to performance analysis of non-residential buildings

由 Miller, Clayton, Nagy, Zoltan, Schlueter, Arno
出版 2021

Build2Vec: Building Representation in Vector Space

由 Abdelrahman, Mahmoud, Chong, Adrian, Miller, Clayton
出版 2021

Islands of misfit buildings: Detecting uncharacteristic electricity use behavior using load shape clustering

由 Quintana, Matias, Arjunan, Pandarasamy, Miller, Clayton
出版 2021

Data mining cubes for buildings, a generic framework for multidimensional analytics of building performance data

由 Leprince, Julien, Miller, Clayton, Zeiler, Wim
出版 2022

Twenty Years of Building Performance Analysis Trends: A Topic Modeling Analysis of the Bldg-Sim Email List Archive

由 Miller, Clayton, Quintana, Matias, Glazer, Jason
出版 2022

Personal thermal comfort models using digital twins: Preference prediction with BIM-extracted spatial-temporal proximity data from Build2Vec

由 Abdelrahman, Mahmoud M, Chong, Adrian, Miller, Clayton
出版 2022

Gradient boosting machines and careful pre-processing work best: ASHRAE Great Energy Predictor III lessons learned

由 Miller, Clayton Carl, Hao, Liu, Fu, Chun
出版 2023

A workflow for managing building information and performance data using virtual reality: an alternative to BIM for existing buildings?

由 Rysanek, Adam, Miller, Clayton Carl, Schlueter, Arno
出版 2021

Unsupervised load shape clustering for urban building performance assessment

由 Fonseca, Jimeno A, Miller, Clayton, Schlueter, Arno
出版 2021

Design with Comfort: Expanding the psychrometric chart with radiation and convection dimensions

由 Teitelbaum, Eric, Jayathissa, Prageeth, Miller, Clayton, Meggers, Forrest
出版 2022

Personal comfort models based on a 6-month experiment using environmental parameters and data from wearables

由 Tartarini, Federico, Schiavon, Stefano, Quintana, Matias, Miller, Clayton
出版 2023

Energy balances, thermal performance, and heat stress: Disentangling occupant behaviour and weather influences in a Dutch net-zero energy neighborhood

由 Kazmi, Hussain, Keijsers, Merel, Mehmood, Fahad, Miller, Clayton
出版 2022