Analysis of infrasound characteristics and intelligent inversion method for debris flow discharge
Infrasound technology has been widely applied in debris flow monitoring and early warning.Certain characteristics of debris flow infrasound can reflect the debris flow discharge to a certain extent.Debris flow discharge is an important parameter for evaluating the scale of debris flow,and the accurate prediction of debris flow discharge is of great significance for debris flow monitoring and early warning.Based on the key physical parameters that affect the infrasound characteristics of debris flow,a quantitative ratio water tank experiment is conducted to simulate the physical process of infrasound generated by debris flow.Infrasound signals are collected and the debris flow discharge is measured.By analyzing the correlation between the debris flow discharge and the infrasound of debris flow,the influence pattern of flow discharge on the infrasound characteristics is revealed.After feature extraction and selection,infrasound characteristics that can characterize the flow discharge of debris flow are refined and a feature vector set is constructed.By comparing the performance of KNN,neural networks,random forests,and GBDT algorithms in flow discharge prediction,an intelligent inversion model for debris flow discharge with high prediction accuracy is constructed.This intelligent inversion model can achieve effective prediction of debris flow discharge,providing richer alarm information for debris flow infrasound monitoring.
NETL
NSTL
万方数据
维普
