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SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

机译:人工神经网络在泥石流模拟与预测中的应用

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摘要

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural hazard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting debris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and useful in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time series of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collected in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.
机译:泥石流是自然灾害最具破坏性的现象之一。最近,主要的自然灾害夺走了人类的生命和财产,归因于世界上的泥石流。已经提出了几种预测泥石流的实用方法,但是,由于泥石流的随机性和非线性特征,这些方法的准确性不足以实际应用。事实证明,人工神经网络在开发非线性系统模型中是可行且有用的。另一方面,基于收集的历史数据的时间序列预测未来行为也是许多科学应用中的重要工具。在这项研究中,我们提出了一个三层前馈神经网络模型,根据在中国云南省北部的江家沟谷收集的时间序列数据,预测泥石流激增。使用所提出的方法对泥石流进行仿真和预测表明,该模型是可行的,但是还需要进一步的研究。

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