Deep learning-based method for weather forecasting: A case study in Itoshima
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866910378506584064 |
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| author | Cheng, Yuzhong Nguyen, Linh Thi Hoai Ozaki, Akinori Ta, Ton Viet |
| author_facet | Cheng, Yuzhong Nguyen, Linh Thi Hoai Ozaki, Akinori Ta, Ton Viet |
| contents | Accurate weather forecasting is of paramount importance for a wide range of practical applications, drawing substantial scientific and societal interest. However, the intricacies of weather systems pose substantial challenges to accurate predictions. This research introduces a multilayer perceptron model tailored for weather forecasting in Itoshima, Kyushu, Japan. Our meticulously designed architecture demonstrates superior performance compared to existing models, surpassing benchmarks such as Long Short-Term Memory and Recurrent Neural Networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_14918 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Deep learning-based method for weather forecasting: A case study in Itoshima Cheng, Yuzhong Nguyen, Linh Thi Hoai Ozaki, Akinori Ta, Ton Viet Machine Learning Accurate weather forecasting is of paramount importance for a wide range of practical applications, drawing substantial scientific and societal interest. However, the intricacies of weather systems pose substantial challenges to accurate predictions. This research introduces a multilayer perceptron model tailored for weather forecasting in Itoshima, Kyushu, Japan. Our meticulously designed architecture demonstrates superior performance compared to existing models, surpassing benchmarks such as Long Short-Term Memory and Recurrent Neural Networks. |
| title | Deep learning-based method for weather forecasting: A case study in Itoshima |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2403.14918 |