Landslide displacement prediction method and system based on sliding window method and Stacking ensemble learning algorithm

The invention discloses a sliding window method and Stacking ensemble learning algorithm-based landslide displacement prediction method and system. The method comprises the steps of collecting landslide displacement data of each monitoring point, and decomposing the data into trend term data and periodic term data by adopting a moving average method; constructing a data set according to the data, preliminarily screening candidate input factors, and performing Pearson correlation coefficient analysis on the candidate input factors and the periodic term data to obtain model input factors; decomposing the model input factor into a fitting set and a prediction set, and performing prediction based on a sliding window method and a Stacking integrated deep learning algorithm to obtain a periodic term displacement prediction result; predicting the trend term data by using a support vector regression algorithm to obtain a trend term displacement prediction result, and adding the periodic term displacement prediction r