文献
J-GLOBAL ID:202002223152161268
整理番号:20A2068054
早期森林火災救助のための自然にヒントを得たアルゴリズムを用いたアンサンブルフレームワークのためのベンチマークデータセット【JST・京大機械翻訳】
A benchmark dataset for ensemble framework by using nature inspired algorithms for the early-stage forest fire rescue
著者 (5件):
Zhang HongGuang
(School of Electronic Engineering, Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing, China)
,
Liang ZiHan
(School of Electronic Engineering, Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing, China)
,
Liu HuaJian
(School of Electronic Engineering, Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing, China)
,
Wang Rui
(School of Electronic Engineering, Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing, China)
,
Liu YuanAn
(School of Electronic Engineering, Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing, China)
資料名:
Data in Brief
(Data in Brief)
巻:
31
ページ:
Null
発行年:
2020年
JST資料番号:
W3049A
ISSN:
2352-3409
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)