[S21] 機械学習

[153] APPLICATION OF RADIAL-BASIS FUNCTION NETWORK TO CHARACTERIZE FUTURE RAINFALL PRONE TO SEDIMENT HAZARDS IN A CHANGING CLIMATE

WU Ying-Hsin¹、*YAMAJI Akihiko²、NAKAKITA Eiichi³ (1. Disaster Prevention Research Institute, Kyoto University、2. Japan Weather Association、3. Disaster Prevention Research Institute, Kyoto University)

キーワード：climate change、NHRCM、Radar-AMeDAS、radial basis function network