A meta analysis of the status of AI in environmental computer science
| dc.contributor.author | Sinwell, Lukas | |
| dc.contributor.author | Bruns, Julian | |
| dc.contributor.author | Budde, Matthias | |
| dc.contributor.author | Abecker, Andreas | |
| dc.date.accessioned | 2021-12-14T10:57:21Z | |
| dc.date.available | 2021-12-14T10:57:21Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Artificial Intelligence is hyped as one of the key enablers of the future which will help to solve key challenges of humanity. The research field which already addresses many of those challenges is Environmental (Computer) Science. Therefore, it seems like a natural fit to combine both fields. AI can provide algorithms and methods to ease the computations and extend the existing (simulation) models of the environmental sciences. The environmental sciences already have in-depth knowledge of the problems at hand, can evaluate and interpret both the relative importance of input data as well as the results. However, to achieve this synergy, a strong foundation and knowledge of previous work is needed. This work aims to contribute to this foundation by providing a data-driven overview of AI-based research activities in the field of environmental computer science. | en |
| dc.identifier.doi | 10.18420/informatik2021-027 | |
| dc.identifier.isbn | 978-3-88579-708-1 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/37690 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik, Bonn | |
| dc.relation.ispartof | INFORMATIK 2021 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-314 | |
| dc.subject | AI | |
| dc.subject | Computational Sustainability | |
| dc.subject | Environmental Computer Science | |
| dc.subject | Meta Analysis | |
| dc.title | A meta analysis of the status of AI in environmental computer science | en |
| gi.citation.endPage | 347 | |
| gi.citation.startPage | 333 | |
| gi.conference.date | 27. September - 1. Oktober 2021 | |
| gi.conference.location | Berlin | |
| gi.conference.sessiontitle | 2. Workshop Künstliche Intelligenz in der Umweltinformatik (KIUI-2021) |
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