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%0 Conference Paper
%1 schreiber2019generative
%A Schreiber, Jens
%A Jessulat, Maik
%A Sick, Bernhard
%B International Conference on Artificial Neural Networks and Machine Learning (ICANN): Image Processing
%C Cham
%D 2019
%I Springer
%K imported
%P 550--564
%R 10.1007/978-3-030-30508-6_44
%T Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic
%@ 978-3-030-30508-6
@inproceedings{schreiber2019generative,
added-at = {2022-01-07T10:37:59.000+0100},
address = {Cham},
author = {Schreiber, Jens and Jessulat, Maik and Sick, Bernhard},
biburl = {https://www.bibsonomy.org/bibtex/266653ae1e2a921bc258f6bc2415afd56/ies},
booktitle = {International Conference on Artificial Neural Networks and Machine Learning (ICANN): Image Processing},
doi = {10.1007/978-3-030-30508-6_44},
interhash = {9aea10c8ed69a3fbb172efd57547fdc9},
intrahash = {66653ae1e2a921bc258f6bc2415afd56},
isbn = {978-3-030-30508-6},
keywords = {imported},
pages = {550--564},
publisher = {Springer},
timestamp = {2022-01-07T10:37:59.000+0100},
title = {Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic},
year = 2019
}