Shen, C. and Xue, S., 2018. Displacement prediction of rainfall-induced landslide based on machine learning. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 272–276. Coconut Creek (Florida), I SSN 0749-0208.
China is a country with frequent landslides, and landslides damage the infrastructure, which has seriously affected the modernization of the country and the lives of the people. There are quite a lot of cities and villages in China suffering from landslides and the average annual economic losses are numerous. Meanwhile, landslides also affect the key construction projects in many countries. According to statistics, about 90% of the landslides are related to rainfall. Under this background, how to predict the rainfall-induced landslide has become an urgent problem to be solved at present. Taking the monitoring area of the Baijiabao landslide of the Three Gorges Reservoir Area as the research object, combining the machine learning of the genetic algorithm and support vector regression (SVR) method, a rainfall-induced landslide displacement model is established to predict the displacement of the rainfall-induced landslide, which is to provide some reference value for landslide prediction.