| SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK |
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| 作者姓名： | WANGXie-kang HUANGEr CUIPeng |
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| 作者单位： | 1. State Key Laboratory of Hydraulics on High Speed Flows，Sichuan University，Chengdu 610065，P. R. China: 2. Institute of Mountain Hazards & Environment，Chinese Academy of Sciences，Chengdu 610041，P. R. China |
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| 基金项目： | UndertheauspicesoftheNationalNaturalScienceFoundationofChina(No.40025103) |
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| 摘 要： | Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris 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 use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries 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 collect-ed 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.
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| 关 键 词： | 泥石流 人工神经网络 时间序列分析 模拟 |
| 收稿时间： | 25 December 2002 |
Simulation and prediction of debris flow using artificial neural network |
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| WANGXie-kang HUANGEr CUIPeng.SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK[J].Chinese Geographical Science,2003,13(3):262-266. |
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| Authors: | Wang Xie-kang Huang Er Cui Peng |
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| Institution: | (1) State Key Laboratory of Hydraulics on High Speed Flows, Sichuan University, 610065 Chengdu, P. R. China;(2) Institute of Mountain Hazards & Environment, Chinese Academy of Sciences, 610041 Chengdu, P. R. China |
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| Abstract: | 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. |
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| Keywords: | debris flow time series artificial neural network |
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