ニューラルネットワークを用いたリアルタイム高潮予測における学習パラメータの感度分析に関する研究

抄録

In the paper, the sensitivity of real-time storm surge forecast models to the input parameters is described based on the artificial neural network in order to predict the storm surge at Sakai Minato in the Sanin coast. In addition, the forecast time spans of 01, 02, 03, 04, 05, 12 and 24 hours are investigated. The study reveals that the real-time forecast model for the 24 forecast successfully predicted the observation at Sakai Minato. The performance of the real time forecast model for the 24h forecast was best when using the data set consisting of the storm surge, the sea level pressure, the depression rate of the sea level pressure and the typhoon position.