Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Meritxell Gómez-Omella"'
Publikováno v:
Proceedings, Vol 65, Iss 1, p 24 (2021)
RESPOND proposes an Artificial Intelligent (AI) system to assist residential consumers that would like to make use of Demand Response (DR) and incorporate it into their energy management systems. The proposed system considers the forecast energy cons
Externí odkaz:
https://doaj.org/article/f0b5710339a042f58d8d04ee0d0956a1
Autor:
Iker Esnaola-Gonzalez, Meritxell Gómez-Omella, Susana Ferreiro, Izaskun Fernandez, Ignacio Lázaro, Elena García
Publikováno v:
Sensors, Vol 20, Iss 6, p 1549 (2020)
As a consequence of the projected world population growth, world meat consumption is expected to grow. Therefore, meat production needs to be improved, although it cannot be done at any cost. Maintaining the health and welfare status of animals at op
Externí odkaz:
https://doaj.org/article/bbd3cd71e3a241a2a87c7e415d123477
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030637989
SGAI Conf.
SGAI Conf.
Demand Response (DR) can contribute towards the energy efficiency in buildings, which is one of the major concerns among governments, scientists, and researchers. DR programs rely on the anticipation to electric demand peaks, for which the developmen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e1d7f18dfc30b564479adcf7b036d695
https://doi.org/10.1007/978-3-030-63799-6_18
https://doi.org/10.1007/978-3-030-63799-6_18
Publikováno v:
Energy and Buildings. 253:111396
This work presents a case study of Big Data and Machine Learning whose objective is to improve energy Demand Response (DR) programs by providing accurate energy demand forecasts. Given the present state of the art, this research work introduces the p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5e2418aaf4d6a34ff7a5907020b6f37
https://doi.org/10.1016/j.enbuild.2021.111396
https://doi.org/10.1016/j.enbuild.2021.111396
Autor:
Meritxell Gómez-Omella, Cristobal Ruiz-Carcel, Susana Ferreiro, Aitor Arnaiz, Kerman López de Calle-Etxabe, Andrew Starr, Basilio Sierra
Publikováno v:
Computers in Industry. 123:103339
The advantages of condition based maintenance over alternative maintenance strategies have been widely proven. Detection, diagnosis and prognostic algorithms enable the optimization of repair schedules while avoiding breakdowns and downtimes. However
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d78796c02eb2bfa4881467d6fc7f41d
https://doi.org/10.1016/j.compind.2020.103339
https://doi.org/10.1016/j.compind.2020.103339
Autor:
Martinez-Rico, Jon, Zulueta, Ekaitz, de Argandona, Ismael Ruiz, Armendia, Mikel, Fernandez-Gamiz, Unai
Publikováno v:
IEEE Transactions on Industry Applications; Sep/Oct2022, Vol. 58 Issue 5, p5624-5634, 11p
Autor:
Esnaola-Gonzalez, Iker1 (AUTHOR) iker.esnaola@tekniker.es, Gómez-Omella, Meritxell1,2 (AUTHOR) susana.ferreiro@tekniker.es, Ferreiro, Susana1 (AUTHOR) izaskun.fernandez@tekniker.es, Fernandez, Izaskun1 (AUTHOR) ignacio.lazaro@tekniker.es, Lázaro, Ignacio1 (AUTHOR) elena.garcia@tekniker.es, García, Elena1 (AUTHOR)
Publikováno v:
Sensors (14248220). 3/15/2020, Vol. 20 Issue 6, p1549. 1p.
Autor:
Max Bramer, Richard Ellis
This book constitutes the proceedings of the 40th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2020, which was supposed to be held in Cambridge, UK, in December 2020. The conference was held v