Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks
Rapid and accurate hazard prediction is important for prompt evacuation and casualty reduction during natural disasters. Here, the authors present an AI-enabled tsunami forecasting approach, which provided rapid and accurate early warnings.
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Nature Portfolio
2021
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oai:doaj.org-article:b2dbf73069984e17b4e1bde9bf7038c02021-12-02T14:30:27ZEarly forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks10.1038/s41467-021-22348-02041-1723https://doaj.org/article/b2dbf73069984e17b4e1bde9bf7038c02021-04-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-22348-0https://doaj.org/toc/2041-1723Rapid and accurate hazard prediction is important for prompt evacuation and casualty reduction during natural disasters. Here, the authors present an AI-enabled tsunami forecasting approach, which provided rapid and accurate early warnings.Fumiyasu MakinoshimaYusuke OishiTakashi YamazakiTakashi FurumuraFumihiko ImamuraNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-10 (2021) |
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DOAJ |
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DOAJ |
| language |
EN |
| topic |
Science Q |
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Science Q Fumiyasu Makinoshima Yusuke Oishi Takashi Yamazaki Takashi Furumura Fumihiko Imamura Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks |
| description |
Rapid and accurate hazard prediction is important for prompt evacuation and casualty reduction during natural disasters. Here, the authors present an AI-enabled tsunami forecasting approach, which provided rapid and accurate early warnings. |
| format |
article |
| author |
Fumiyasu Makinoshima Yusuke Oishi Takashi Yamazaki Takashi Furumura Fumihiko Imamura |
| author_facet |
Fumiyasu Makinoshima Yusuke Oishi Takashi Yamazaki Takashi Furumura Fumihiko Imamura |
| author_sort |
Fumiyasu Makinoshima |
| title |
Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks |
| title_short |
Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks |
| title_full |
Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks |
| title_fullStr |
Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks |
| title_full_unstemmed |
Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks |
| title_sort |
early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/b2dbf73069984e17b4e1bde9bf7038c0 |
| work_keys_str_mv |
AT fumiyasumakinoshima earlyforecastingoftsunamiinundationfromtsunamiandgeodeticobservationdatawithconvolutionalneuralnetworks AT yusukeoishi earlyforecastingoftsunamiinundationfromtsunamiandgeodeticobservationdatawithconvolutionalneuralnetworks AT takashiyamazaki earlyforecastingoftsunamiinundationfromtsunamiandgeodeticobservationdatawithconvolutionalneuralnetworks AT takashifurumura earlyforecastingoftsunamiinundationfromtsunamiandgeodeticobservationdatawithconvolutionalneuralnetworks AT fumihikoimamura earlyforecastingoftsunamiinundationfromtsunamiandgeodeticobservationdatawithconvolutionalneuralnetworks |
| _version_ |
1718391214204518400 |