ESTIMATION OF PREDICTION MODEL FOR ROAD CLOSED TRAINED THE DATA OF HEAVY RAIN IN JULY 2020

Abstract

It is important to predict the amount of precipitation that makes roads closed due to landslide disasters to reduce human damage and secure evacuation routes during heavy rain. This study attempted to estimate a prediction model for road closed that trained the data of heavy rain in July 2020 by using the passable route map as labels in machine learning. However, the estimated model could not predict the labels of road closed and it was found that the estimated model was not available for the prediction model. The reason for the result may be there were mistakes in the labeling process and that only the topographical information and rainfall information were not sufficient as input data.