Big Geospatial Data and Data-Driven Methods for Urban Dengue Risk Forecasting: A Review
With advancements in big geospatial data and artificial intelligence, multi-source data and diverse data-driven methods have become common in dengue risk prediction. Understanding the current state of data and models in dengue risk prediction enables the implementation of efficient and accurate pred...
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| Главные авторы: | , |
|---|---|
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI AG
2022-10-01
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| Серии: | Remote Sensing |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/2072-4292/14/19/5052 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
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