文献
J-GLOBAL ID:202102211951324385
整理番号:21A0874007
遺伝的アルゴリズムを用いた時系列データを予測するための最適スタックアンサンブル深層学習モデル-エーロゾル粒子数濃度への適用【JST・京大機械翻訳】
An Optimal Stacked Ensemble Deep Learning Model for Predicting Time-Series Data Using a Genetic Algorithm-An Application for Aerosol Particle Number Concentrations
著者 (8件):
Surakhi Ola M.
(Department of Computer Science, The University of Jordan, Amman 11942, Jordan)
,
Zaidan Martha Arbayani
(Institute for Atmospheric and Earth System Research (INAR/Physics), University of Helsinki, FI-00014 Helsinki, Finland)
,
Zaidan Martha Arbayani
(Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China)
,
Serhan Sami
(Department of Computer Science, The University of Jordan, Amman 11942, Jordan)
,
Salah Imad
(Department of Computer Science, The University of Jordan, Amman 11942, Jordan)
,
Hussein Tareq
(Institute for Atmospheric and Earth System Research (INAR/Physics), University of Helsinki, FI-00014 Helsinki, Finland)
,
Hussein Tareq
(Department Material Analysis and Indoor Chemistry, Fraunhofer WKI, D-38108 Braunschweig, Germany)
,
Hussein Tareq
(Department of Physics, The University of Jordan, Amman 11942, Jordan)
資料名:
Computers (Web)
(Computers (Web))
巻:
9
号:
4
ページ:
89
発行年:
2020年
JST資料番号:
U7165A
ISSN:
2073-431X
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
スイス (CHE)
言語:
英語 (EN)