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LONG-TERM PROJECTION OF STORM SURGE CHANGE BY NEURAL NETWORK BASED ON STOCHASTIC TROPICAL CYCLONE MODEL
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- IWABE Shiori
- 三井物産株式会社
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- MORI Nobuhito
- 京都大学 防災研究所
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- NAKAJO Sota
- 大阪市立大学 大学院工学研究科
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- YASUDA Tomohiro
- 関西大学 都市環境工学部
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- MASE HAJIME
- 京都大学 防災研究所
Bibliographic Information
- Other Title
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- 確率台風モデル，高潮モデルおよびニューラルネットワークを用いた高潮偏差の長期評価
- カクリツ タイフウ モデル,タカシオ モデル オヨビ ニューラルネットワーク オ モチイタ タカシオ ヘンサ ノ チョウキ ヒョウカ
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Description
A long-term assessment of storm surge using the stochastic typhoon model (STM) is one of the secured methodology with the large number of samples of the reproducibility is desired if we can estimate storm surge from STM. This study has improved statistical maximum storm surge model, which uses only typhoon information, in the three major bays using artificial neural network (NN). In order to estimate long-term changes in storm surge characteristics under future climate conditions, NN uses STM and climate database for Policy Decision making for Future climate change (d4PDF). The long-term impact assessments of storm surge using several scenarios are compared.
Journal
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- Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering)
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Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering) 72 (2), I_1465-I_1470, 2016
Japan Society of Civil Engineers