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Influence of input parameters on artificial neural networks for off-grid solar photovoltaic power forecasting

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Author:Aminu Bugaje, Akhilesh Yadav, Kedar MehtaORCiD, Felicia Ojinji, Mathias EhrenwirthORCiD, Christoph TrinklORCiD, Wilfried Zörner
Language:English
Document Type:Conference Paper
Conference:NEIS 2021: Conference on Sustainable Energy Supply and Energy Storage Systems, Hamburg (Germany), 13.-14.09.2021
Year of first Publication:2021
published in (English):NEIS 2021
Publisher:VDE Verlag
Place of publication:Berlin
ISBN:978-3-8007-5651-3
ISBN:978-3-8007-5652-0
First Page:135
Last Page:141
Review:editorial review
Open Access:ja
Tag:artificial neural networks; correlation coefficient; mean absolute error; mean squared error; off-grid solar system; solar power forecast
URL:https://ieeexplore.ieee.org/document/9698257
URL:https://www.vde-verlag.de/proceedings-en/565651017.html
Faculties / Institutes / Organizations:Fakultät Maschinenbau
Institut für neue Energie-Systeme (InES)
Release Date:2022/03/11