文献
J-GLOBAL ID:201702254990680380
整理番号:17A0969945
NILMにおける事象検出法のBayes最適化とロバスト性について【Powered by NICT】
On the Bayesian optimization and robustness of event detection methods in NILM
著者 (5件):
De Baets Leen
(Department of Information Technology, Ghent University - imec, Technologiepark-Zwijnaarde 15, 9052 Ghent, Belgium)
,
Ruyssinck Joeri
(Department of Information Technology, Ghent University - imec, Technologiepark-Zwijnaarde 15, 9052 Ghent, Belgium)
,
Develder Chris
(Department of Information Technology, Ghent University - imec, Technologiepark-Zwijnaarde 15, 9052 Ghent, Belgium)
,
Dhaene Tom
(Department of Information Technology, Ghent University - imec, Technologiepark-Zwijnaarde 15, 9052 Ghent, Belgium)
,
Deschrijver Dirk
(Department of Information Technology, Ghent University - imec, Technologiepark-Zwijnaarde 15, 9052 Ghent, Belgium)
資料名:
Energy and Buildings
(Energy and Buildings)
巻:
145
ページ:
57-66
発行年:
2017年
JST資料番号:
A0199A
ISSN:
0378-7788
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)