A comprehensive review of deep learning applications in hydrology and water resources
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water resources management, and climate change. Combine...
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Détails bibliographiques
| Publié dans: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 82(2020), 12 vom: 31. Dez., Seite 2635-2670
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| Auteur principal: |
Sit, Muhammed
(Auteur) |
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| Autres auteurs: |
Demiray, Bekir Z,
Xiang, Zhongrun,
Ewing, Gregory J,
Sermet, Yusuf,
Demir, Ibrahim |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2020
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| Accès à la collection: | Water science and technology : a journal of the International Association on Water Pollution Research
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| Sujets: | Journal Article
Systematic Review |
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