文献
J-GLOBAL ID:202202273108848445
整理番号:22A0900093
FRCMで曲げ補強されたRC梁の曲げ耐力予測のための説明可能な機械学習モデルと信頼性解析【JST・京大機械翻訳】
Explainable machine learning model and reliability analysis for flexural capacity prediction of RC beams strengthened in flexure with FRCM
著者 (5件):
Wakjira Tadesse G.
(Department of Civil and Architectural Engineering, College of Engineering, Qatar University, P.O. Box 2713, Doha, Qatar)
,
Wakjira Tadesse G.
(Applied Laboratory for Advanced Materials & Structures (ALAMS), School of Engineering, The University of British Columbia, Kelowna, BC V1V 1V7, Canada)
,
Ibrahim Mohamed
(Department of Civil and Architectural Engineering, College of Engineering, Qatar University, P.O. Box 2713, Doha, Qatar)
,
Ebead Usama
(Department of Civil and Architectural Engineering, College of Engineering, Qatar University, P.O. Box 2713, Doha, Qatar)
,
Alam M. Shahria
(Applied Laboratory for Advanced Materials & Structures (ALAMS), School of Engineering, The University of British Columbia, Kelowna, BC V1V 1V7, Canada)
資料名:
Engineering Structures
(Engineering Structures)
巻:
255
ページ:
Null
発行年:
2022年
JST資料番号:
C0709B
ISSN:
0141-0296
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)