%0 Journal Article %1 yan2024framework %A Yan, Chang %A Xu, Shengfeng %A Sun, Zhenxu %A Lutz, Thorsten %A Guo, Dilong %A Yang, Guowei %D 2024 %I Elsevier %J Applied energy %K %P 123719 %R 10.1016/j.apenergy.2024.123719 %T A framework of data assimilation for wind flow fields by physics-informed neural networks %V 371

@article{yan2024framework, added-at = {2025-04-25T09:18:51.000+0200}, author = {Yan, Chang and Xu, Shengfeng and Sun, Zhenxu and Lutz, Thorsten and Guo, Dilong and Yang, Guowei}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/28567b25c0d659a184d4614715b5f6249/unibiblio}, doi = {10.1016/j.apenergy.2024.123719}, interhash = {ff216acba83e1ba41504cc1a95115512}, intrahash = {8567b25c0d659a184d4614715b5f6249}, issn = {{0306-2619} and {1872-9118}}, journal = {Applied energy}, keywords = {}, language = {eng}, pages = 123719, publisher = {Elsevier}, researcherid-numbers = {Yang, Guowei/AAY-5880-2021}, timestamp = {2025-04-25T07:18:51.000+0200}, title = {A framework of data assimilation for wind flow fields by physics-informed neural networks}, unique-id = {WOS:001339518700001}, volume = 371, year = 2024 }