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1 Ergebnisse
1
Machine Learning for Drought Prediction; Review, Bibliometr..:
, In:
2023 IEEE 27th International Conference on Intelligent Engineering Systems (INES)
,
Mosavi, Amirhosein
;
Ardabili, Sina
- p. 000095-000104 , 2023
Link:
https://doi.org/10.1109/INES59282.2023.10297771
RT T1 <cTitle>2023 IEEE 27th International Conference on Intelligent Engineering Systems (INES)</cTitle>: T1 <Title>Machine Learning for Drought Prediction; Review, Bibliometric Analysis, and Models Evaluation</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10297771&Exemplar=1&LAN=DE A1 Mosavi, Amirhosein A1 Ardabili, Sina YR 2023 K1 Surveys K1 Adaptation models K1 Systematics K1 Biological system modeling K1 Droughts K1 Taxonomy K1 Machine learning K1 Climate change K1 drought prediction K1 drought K1 natural disaster K1 machine learning K1 deep learning K1 artificial intelligence K1 big data K1 data science K1 hydrology K1 extreme events K1 XAI K1 drought modeling K1 hydrological models SP 000095 OP 000104 LK http://dx.doi.org/https://doi.org/10.1109/INES59282.2023.10297771 DO https://doi.org/10.1109/INES59282.2023.10297771 SF ELIB - SuUB Bremen
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