| dc.contributor.author | Jiang, Junjie | |
| dc.contributor.author | Huang, Zi-Gang | |
| dc.contributor.author | Grebogi, Celso | |
| dc.contributor.author | Lai, Ying-Cheng | |
| dc.date.accessioned | 2022-04-12T08:37:01Z | |
| dc.date.available | 2022-04-12T08:37:01Z | |
| dc.date.issued | 2022-06-01 | |
| dc.identifier | 214043111 | |
| dc.identifier | a208a913-faa8-4118-b7a9-f631e6b88645 | |
| dc.identifier | 85128823138 | |
| dc.identifier.citation | Jiang , J , Huang , Z-G , Grebogi , C & Lai , Y-C 2022 , ' Predicting extreme events from data using deep machine learning : when and where ' , Physical Review Research , vol. 4 , no. 2 , 023028 . https://doi.org/10.1103/PhysRevResearch.4.023028 | en |
| dc.identifier.issn | 2643-1564 | |
| dc.identifier.other | ArXiv: http://arxiv.org/abs/2203.17155v1 | |
| dc.identifier.other | ORCID: /0000-0002-9811-4617/work/111385184 | |
| dc.identifier.uri | https://hdl.handle.net/2164/18388 | |
| dc.description | ACKNOWLEDGMENTS The work at Arizona State University was supported by AFOSR under Grant No. FA9550-21-1-0438 and by ONR under Grant No. N00014-21-1-2323. The work at Xi’an Jiaotong University was supported by the National Key R&D Program of China (Grant No. 2021ZD0201300), National Natural Science Foundation of China (Grant No. 11975178), and K. C. Wong Education Foundation. | en |
| dc.format.extent | 14 | |
| dc.format.extent | 7095520 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Physical Review Research | en |
| dc.subject | QC Physics | en |
| dc.subject.lcc | QC | en |
| dc.title | Predicting extreme events from data using deep machine learning : when and where | en |
| dc.type | Journal article | en |
| dc.contributor.institution | University of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB) | en |
| dc.contributor.institution | University of Aberdeen.Environment and Food Security | en |
| dc.contributor.institution | University of Aberdeen.Physics | en |
| dc.description.status | Peer reviewed | en |
| dc.identifier.doi | 10.1103/PhysRevResearch.4.023028 | |
