Simulation and Prediction Algorithm for the Whole Process of Debris Flow Based on Multiple Data Integration

Abstract

In order to solve the problems of large errors and low accuracy in debris-flow forecasting, the simulation and prediction algorithm for the whole process of debris flow based on multiple data integrations is studied. The middleware method is used to integrate multiple GIS data sets, and the GIS spatial database after multiple data integrations is used to provide the basis of data for the whole process simulation and prediction of debris flow. The spatial cellular simulation model of debris flow is built using the cellular automatic mechanism. The improved kernel principal component analysis method is used to reduce the dimension of debris-flow prediction index data. The reduced dimension index data is input into the support vector machine, and the support vector machine is used to output the prediction results of debris flow in the space cell simulation model of debris flow. Through the simulation visualization technology, the dynamic display of the simulation prediction of the whole process of debris flow is carried out. The experimental results show that the algorithm can realize the simulation of the whole process of debris-flow changes, that the prediction results of debris flow are close to the actual results, and that the error is less than 5%, which improves the prediction accuracy of debris flow and can be used as the auxiliary basis for relevant decision-making departments.