Prediction on hazardous areas of debris flow based on neural network

Abstract:

By in-depth investigation and analysis of debris flows in Jinsha River watershed,the index values of several factors mainly the affecting hazardous areas of debris flow are extracted to predict the hazardous areas more objectively.The capability learning of improved BP neural network is used to predict the sensitivity of these factors.The slope of error curve is presented as the quantitative indicator of sensitivity.The factors affecting hazardous areas of various types of debris flows are assessed with the error coefficient and the conclusions are analyzed from the view of fluid mechanics.A new formula is proposed to improve the traditional forecasting model.In the example simulation,the improved model gets more accurate forecasting results.The difference between relative errors calculated by the improved model and the traditional model is 4.54 at most.