Seepage Pressure Neural Network Monitoring Model for  High Slope Considering the effect of Rainfall

Abstract

Abstract:

In order to describe the seepage pressure regular pattern of high slope affected by rainfall, and get to know its safety state, integral rainfall factor was presented into these analysis. The monitoring model frame based on Radial basis function (RBF) artificial neural network was constructed considering the integral rainfall factor. RBF centers were confirmed by the fuzzy cmeans algorithm (FCM) with the observed data. Application shows that the integral rainfall factor can effectively reflect the rainfall effect, and the monitoring model achieve good training and forecasting results.

Key words: high slope, seepage pressure, rainfall, radial basis function (RBF), monitoring model

CLC Number:

TU 454

HUANG Ming1,LIU Jun2. Seepage Pressure Neural Network Monitoring Model for High Slope Considering the effect of Rainfall[J]. Journal of Shanghai Jiaotong University, 2013, 47(10): 1548-1551.

References

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Seepage Pressure Neural Network Monitoring Model for High Slope Considering the effect of Rainfall

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