Recommendation of Similar Landslide Cases Based on Landslide Profile

In landslide disaster prevention project, landslide profile is an important research object, which contains rich geological information of landslide. When we get the profile image of the landslide, if we can recommend several landslide cases with similar geological characteristics by the landslide profile image for research, the landslide disaster prevention project can be carried out quickly. In this paper, we propose a recommendation system based on similarity of landslide geological characteristics. The recommendation system is divided into two steps. Firstly, we construct a classification model to obtain the categories of landslide geological characteristics from the profile image by random forest algorithm and supervised machine learning approach. Then, according to the categories of landslide geological characteristics, the landslide case recommended model is constructed, and 5 landslide cases with similar geological characteristics are recommended for the landslide. According to the evaluation index of the recommendation system, the evaluation results show the effectiveness of the recommendation system.