Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Matias Quintana"'
Autor:
Negin Nazarian, Sijie Liu, Manon Kohler, Jason K W Lee, Clayton Miller, Winston T L Chow, Sharifah Badriyah Alhadad, Alberto Martilli, Matias Quintana, Lindsey Sunden, Leslie K Norford
Publikováno v:
Environmental Research Letters, Vol 16, Iss 3, p 034031 (2021)
Global climate is changing as a result of anthropogenic warming, leading to higher daily excursions of temperature in cities. Such elevated temperatures have great implications on human thermal comfort and heat stress, which should be closely monitor
Externí odkaz:
https://doaj.org/article/9d06ebf30f0a427088d9f3002984b271
Publikováno v:
Buildings, Vol 10, Iss 10, p 174 (2020)
Evaluating and optimising human comfort within the built environment is challenging due to the large number of physiological, psychological and environmental variables that affect occupant comfort preference. Human perception could be helpful to capt
Externí odkaz:
https://doaj.org/article/5fb9027eb6cb473c8d898ac0f6b8ae8a
Publikováno v:
Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation.
Publikováno v:
Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation.
Publikováno v:
Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation.
Autor:
Yi Ting Teo, Matias Quintana, Muhammad Zikry Bin Sabarudin, Charlene Tan, Adrian Chong, Clayton Miller
Publikováno v:
Proceedings of the Twentieth ACM Conference on Embedded Networked Sensor Systems.
Publikováno v:
Indoor air, vol 32, iss 11
Personal thermal comfort models are a paradigm shift in predicting how building occupants perceive their thermal environment. Previous work has critical limitations related to the length of the data collected and the diversity of spaces. This paper o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a702886f20448a4d58b8e0f3250a6d5
https://escholarship.org/uc/item/9xd5q2sf
https://escholarship.org/uc/item/9xd5q2sf
Autor:
Matias Quintana, Till Stoeckmann, June Young Park, Marian Turowski, Veit Hagenmeyer, Clayton Miller
Publikováno v:
Energy and Buildings. 286:112930
Autor:
Zoltan Nagy, Gregor Henze, Sourav Dey, Javier Arroyo, Lieve Helsen, Xiangyu Zhang, Bingqing Chen, Kadir Amasyali, Kuldeep Kurte, Ahmed Zamzam, Helia Zandi, Ján Drgoňa, Matias Quintana, Steven McCullogh, June Young Park, Han Li, Tianzhen Hong, Silvio Brandi, Giuseppe Pinto, Alfonso Capozzoli, Draguna Vrabie, Mario Berges, Kingsley Nweye, Thibault Marzullo, Andrey Bernstein
Publikováno v:
Building and Environment. :110435
As buildings account for approximately 40% of global energy consumption and associated greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The increased integration of variable energy sources, such as renewables, introduc
ALDI++: Automatic and parameter-less discord and outlier detection for building energy load profiles
Autor:
Matias Quintana, Till Stoeckmann, June Young Park, Marian Turowski, Veit Hagenmeyer, Clayton Miller
Data-driven building energy prediction is an integral part of the process for measurement and verification, building benchmarking, and building-to-grid interaction. The ASHRAE Great Energy Predictor III (GEPIII) machine learning competition used an e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79b851cdd1181a26183b21d529a02d45
http://arxiv.org/abs/2203.06618
http://arxiv.org/abs/2203.06618