文献
J-GLOBAL ID:201602291331748720
整理番号:16A0967244
物理的手法及び人工ニューラルネットワークを用いた薄膜光電池プラントのエネルギー収率評価
Energy yield estimation of thin-film photovoltaic plants by using physical approach and artificial neural networks
著者 (5件):
Graditi Giorgio
(Italian National Agency for New Technologies, Energy and Sustainable Economic Development, ENEA - Research Center, Piazza E. Fermi 1, 80055 Portici (NA), Italy)
,
Ferlito Sergio
(Italian National Agency for New Technologies, Energy and Sustainable Economic Development, ENEA - Research Center, Piazza E. Fermi 1, 80055 Portici (NA), Italy)
,
Adinolfi Giovanna
(Italian National Agency for New Technologies, Energy and Sustainable Economic Development, ENEA - Research Center, Piazza E. Fermi 1, 80055 Portici (NA), Italy)
,
Tina Giuseppe Marco
(Dipartimento di Ingegneria Elettrica, Elettronica e Informatica, University of Catania, Viale Andrea Doria n. 6, 95125 Catania, Italy)
,
Ventura Cristina
(Dipartimento di Ingegneria Elettrica, Elettronica e Informatica, University of Catania, Viale Andrea Doria n. 6, 95125 Catania, Italy)
資料名:
Solar Energy
(Solar Energy)
巻:
130
ページ:
232-243
発行年:
2016年06月
JST資料番号:
E0099A
ISSN:
0038-092X
CODEN:
SRENA
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)