Earticle

초록

영어

Landslide deformation signal processing is significant for landslide stability analysis. Global Position System (GPS) control networks were built to monitor landslide deformation and acquire landslide displacement time series. It was difficult to predict landslide displacement because of the highly non-linear and non-stationary characteristics contained in displacement time series. A Wavelet Analysis - Radial Basis Function Neural Network (WA-RBFNN) model was proposed to overcome this problem. Firstly, monthly cumulative displacement time series was decomposed into different frequency components using wavelet analysis. Then a RNFNN model was established to forecast each frequency component values. The final prediction results were obtained through the sum of the predictive values of each frequency component. GPS monitoring points ZG325 and ZG326 on Baijiabao landslide in the Three Gorges Reservoir Area were used as study cases. A single RBFNN model was also built as comparison. The experimental results show that GPS control network can monitor landslide deformation accurately and the WA-RBFNN model is of high prediction accuracy. What is more, WA-RBFNN model has better prediction effect than a single RBFNN model.

목차

Abstract
 1. Introduction
 2. Methodology
  2.1. GPS Monitoring Landslide Displacement
  2.2. Wavelet Analysis
  2.3. RBF Neural Network Model
 3. Research Area and Materials
  3.1. Geological Conditions of Baijiabao Landslide
  3.2. GPS Control Network
 4. Experiments and Results
  4.1. Landslide Displacement Normalization
  4.2. ZG324 Displacement Prediction
  4.3 ZG326 Displacement Prediction
 5. Discussion and Conclusions
 Acknowledgements
 References

키워드

저자

• F.M. Huang [ Geological Survey institution, China University of Geosciences (Wuhan), Hubei, CHINA ]
• P. Wu [ Faculty of Information Engineering, China University of Geosciences (Wuhan), Hubei, CHINA, School of Electronics and Information, Yangtze University, Hubei, CHINA ] Correspondong Author
• Y.Y. Ziggah [ Faculty of Information Engineering, China University of Geosciences (Wuhan), Hubei, CHINA ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605