%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 }