Research on landslide hazard prediction system based on dynamic time warping and improved BP neural network
In order to realize the automatic,intelligent and real-time monitoring and forecasting of landslide disaster,the auto-matic control model of landslide disaster prediction system was established based on dynamic time regularization algorithm and back propagation neural network,and the automatic control of landslide disaster prediction system was studied.The model uses the im-proved back propagation neural network to realize the automatic control of the landslide disaster prediction system,and realizes the es-tablishment of the automatic control model of the landslide disaster prediction system.The results show that the percentage error is much less than 10％of the engineering error,and the coefficient of determination is more than 99％,which indicates that there is a good correlation between the predicted value and the real value.The accuracy of the automatic control model of the landslide disaster prediction system is high,which can effectively control the landslide disaster automatically,and provides theoretical basis and techni-cal support for further scientific and effective research,and has a good application prospect.
dynamic time warpingBP neural networklandslide disaster predictionautomatic control
万方数据
维普
