文献
J-GLOBAL ID:201702260081614718
整理番号:17A1247998
教師なしSVM新規性検出とGauss過程モデルを用いたHVAC断層の高度検出【Powered by NICT】
Advanced detection of HVAC faults using unsupervised SVM novelty detection and Gaussian process models
著者 (6件):
Van Every Philip Michael
(Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA)
,
Rodriguez Mykel
(Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA)
,
Jones C. Birk
(Photovoltaics & Grid Integration Department, Sandia National Labs, Albuquerque, NM, USA)
,
Mammoli Andrea Alberto
(Department of Mechanical Engineering, University of New Mexico, Albuquerque, NM, USA)
,
Martinez-Ramon Manel
(Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA)
,
Martinez-Ramon Manel
(Departamento de Teoria de la Senal y Comunicaciones, Universidad Carlos III de Madrid, Leganes, Madrid, Spain)
資料名:
Energy and Buildings
(Energy and Buildings)
巻:
149
ページ:
216-224
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)