文献
J-GLOBAL ID:202202241702973674
整理番号:22A0960311
特徴コスト効率と不均衡データ集合のための深層強化学習を用いた非技術的損失検出【JST・京大機械翻訳】
Non-Technical Loss Detection Using Deep Reinforcement Learning for Feature Cost Efficiency and Imbalanced Dataset
著者 (6件):
Lee Jiyoung
(Department of Electronic Convergence Engineering, Kwangwoon University, Seoul, South Korea)
,
Sun Young Ghyu
(Department of Electronic Convergence Engineering, Kwangwoon University, Seoul, South Korea)
,
Sim Isaac
(Department of Electronic Convergence Engineering, Kwangwoon University, Seoul, South Korea)
,
Kim Soo Hyun
(Department of Electronic Convergence Engineering, Kwangwoon University, Seoul, South Korea)
,
Kim Dong In
(Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South Korea)
,
Kim Jin Young
(Department of Electronic Convergence Engineering, Kwangwoon University, Seoul, South Korea)
資料名:
IEEE Access
(IEEE Access)
巻:
10
ページ:
27084-27095
発行年:
2022年
JST資料番号:
W2422A
ISSN:
2169-3536
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)