دورية أكاديمية
Mutual Information Boosted Precipitation Nowcasting from Radar Images
| العنوان: | Mutual Information Boosted Precipitation Nowcasting from Radar Images |
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| المؤلفون: | Yuan Cao, Danchen Zhang, Xin Zheng, Hongming Shan, Junping Zhang |
| المصدر: | Remote Sensing, Vol 15, Iss 6, p 1639 (2023) |
| بيانات النشر: | MDPI AG, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Science |
| مصطلحات موضوعية: | precipitation nowcasting, mutual information, data imbalance, curriculum learning, Science |
| الوصف: | Precipitation nowcasting has long been a challenging problem in meteorology. While recent studies have introduced deep neural networks into this area and achieved promising results, these models still struggle with the rapid evolution of rainfall and extremely imbalanced data distribution, resulting in poor forecasting performance for convective scenarios. In this article, we evaluate the amount of information in different precipitation nowcasting tasks of varying lengths using mutual information. We propose two strategies: the mutual information-based reweighting strategy (MIR) and a mutual information-based training strategy (time superimposing strategy (TSS)). MIR reinforces neural network models to improve the forecasting accuracy for convective scenarios while maintaining prediction performance for rainless scenarios and overall nowcasting image quality. The TSS strategy enhances the model’s forecasting performance by adopting a curriculum learning-like method. Although the proposed strategies are simple, the experimental results show that they are effective and can be applied to various state-of-the-art models. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 15061639 2072-4292 |
| Relation: | https://www.mdpi.com/2072-4292/15/6/1639; https://doaj.org/toc/2072-4292 |
| DOI: | 10.3390/rs15061639 |
| URL الوصول: | https://doaj.org/article/04b01c18b2ea42c4ab1a298caf0ec429 |
| رقم الأكسشن: | edsdoj.04b01c18b2ea42c4ab1a298caf0ec429 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 15061639 20724292 |
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| DOI: | 10.3390/rs15061639 |