Abstract
Embankment settlement prediction and control is one of the most critical problems for constructing and maintaining the High-speed railway (HSR). The grey model is one of the popular methods used for predicting embankment settlement, because it is of easy-to-use and low computer load. However, it needs many observations and more suit for short-term prediction. The artificial neural network has been widely used in prediction system in many other fields, and it is of robustness and self-adaptive. In this paper, these two methods are combined to give a new Hybrid prediction model to improve the performance and precision of settlement prediction model. The experiments based on real data sets validate the proposed method.
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© 2012 Springer-Verlag Berlin Heidelberg
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Zhang, T.G., Hu, Z.B., Yang, C.F., Liu, Y. (2012). Hybrid Prediction Model for High-Speed Railway Embankment Settlement Using Grey Artificial Neural Network. In: Ni, YQ., Ye, XW. (eds) Proceedings of the 1st International Workshop on High-Speed and Intercity Railways. Lecture Notes in Electrical Engineering, vol 148. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27963-8_18
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DOI: https://doi.org/10.1007/978-3-642-27963-8_18
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