(1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, Sichuan, China;
2. National and Local Joint Engineering Laboratory for Safety Space Information Technology for High-Speed Railway Operation,
Chengdu 611756, Sichuan, China)
Abstract：The settlement of high-speed railway subgrade is characterized by small deformation and large fluctuation of data. Aiming at the problem that the single prediction models such as exponential curve method, three-point method and grey system cannot properly reflect the settlement and deformation law of high-speed railway subgrade in construction period, the improved grey prediction Fourier-Markov residual combination prediction model was used to predict the rule of series superposition of subgrade settlement deformation data, in order to improve the overall accuracy and robustness of the prediction. The proposed model was applied to the measured data of subgrade settlement of a high-speed railway through linear interpolation. The research results show that the combination prediction model is effective. By using Fourier series and Markov state transition matrix, the quadratic combination prediction of the primary residual is predicted, which can better fit the change trend of high-speed railway subgrade settlement monitoring data, and the prediction accuracy has been significantly improved.
张献州1，2，夏晨翕1，陈霄1，蒋英豪1，陈建营1. IGM-FM串联模型在高铁路基沉降预测中的应用[J]. 重庆交通大学学报（自然科学版）, 2020, 39(11): 99-108.
ZHANG Xianzhou1,2，XIA Chenxi1，CHEN Xiao1，JIANG Yinghao1，CHEN Jianying1. Application of Series IGM-FM Combination Model in Prediction of
Subgrade Settlement of High-Speed Railway. Journal of Chongqing Jiaotong University(Natural Science), 2020, 39(11): 99-108.
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2020, Vol. 39 
