Publikationer pr. år
Publikationer pr. år
Projektdetaljer
Beskrivelse
This project aims to design and develop light-AI, including computation-light AI and data-light AI, to enable cognitive power electronics, which holds great potential to address longstanding challenges in operation optimization and condition monitoring of power electronics (PE).
Lægmandssprog
Renewable energy generation and electrification are among the top priorities all over the world. An essential part of renewable energy generation is power electronics (PE) that perform electrical energy conversion. For example, between a wind turbine and the electric grid, a power electronic converter is necessary to provide efficient and reliable grid integration due to the differences in voltage and frequency.
In this project, researchers from the Department of Energy Technology and Department of Computer Science at Aalborg University will combine AI and energy research to design and develop power electronics that can adapt to dynamic operation settings and predict failures.
In this project, researchers from the Department of Energy Technology and Department of Computer Science at Aalborg University will combine AI and energy research to design and develop power electronics that can adapt to dynamic operation settings and predict failures.
| Status | Afsluttet |
|---|---|
| Effektiv start/slut dato | 01/08/2019 → 31/07/2023 |
Samarbejdspartnere
Finansiering
- Villum Fonden: 2.996.278,00 kr.
FN's verdensmål
I 2015 blev FN-landene enige om 17 verdensmål til at bekæmpe fattigdom, beskytte planeten og sikre velstand for alle. Dette projekt bidrager til følgende verdensmål:
Fingerprint
Udforsk forskningsemnerne, som dette projekt berører. Disse etiketter er oprettet på grundlag af de underliggende bevillinger/legater. Sammen danner de et unikt fingerprint.
Publikation
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AutoCTS++: Zero-shot Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting
Wu, X., Wu, X., Yang, B., Zhou, L., Guo, C., Qiu, X., Hu, J., Sheng, Z. & Jensen, C. S., sep. 2024, I: The VLDB Journal. 33, 5, s. 1743-1770 28 s., 5.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
4 Citationer (Scopus)293 Downloads (Pure) -
QCore: Data-Effiicient, On-Device Continual Calibration for Quantized Models
Campos, D., Yang, B., Kieu, T., Zhang, M., Guo, C. & Jensen, C. S., 2024, I: Proceedings of the VLDB Endowment. 17, 11, s. 2708-2721 14 s., 11.Publikation: Bidrag til tidsskrift › Konferenceartikel i tidsskrift › Forskning › peer review
Åben adgangFil5 Citationer (Scopus)36 Downloads (Pure) -
AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting.
Wu, X., Zhang, D., Zhang, M., Guo, C., Yang, B. & Jensen, C. S., 2023, I: Proceedings of the ACM on Management of Data. 1, 1, s. 97:1-97:26Publikation: Bidrag til tidsskrift › Konferenceartikel i tidsskrift › Forskning › peer review
Presse/medier
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Villum Fonden støtter otte projekter med i alt 52,5 mio. kr.
Larsen, K. G., Rasmussen, M. R., Hose, K., Albertsen, M., Wang, H. & Yang, B.
07/05/2020
1 element af Mediedækning
Presse/medie
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Villum Fonden støtter 8 tværfaglige projekter i nyt program
Hose, K., Albertsen, M., Wang, H., Yang, B., Larsen, K. G. & Rasmussen, M. R.
29/03/2020
1 element af Mediedækning
Presse/medie