Abstract
The development law of subgrade settlement is highly nonlinear, unstable and uncertain, so the prediction of subgrade settlement is a difficult problem. In this paper, a prediction model of subgrade settlement based on gene expression programming algorithm (GEP) is proposed, and the algorithm compared with the gray level GM (1,1) model and BP neural network model. The results show that the prediction accuracy of subgrade settlement prediction model that is put forward is better than that of GM (1,1) model and BP neural network model, which provides a new method for subgrade settlement prediction and is of practical significance.
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