在基坑的现代化信息施工过程中,通过建立有效的预测模型,对基坑的变形趋势进行准确的预测,能有效地指导施工,避免工程事故的发生。为实现这一目的,首先,采用GM(1,1)、支持向量机和BP神经网络模型对基坑的变形进行单项预测,并建立了基坑的定权和非定权组合预测模型;其次,利用R/S分析,对基坑的变形趋势进行判断,以验证基坑变形预测的有效性。结果表明:通过组合预测,有效地提高了预测结果的精度及稳定性,其中以BP神经网络组合预测的效果最优,实测值与预测值之间能较好地吻合;同时,基坑具有持续变形的趋势,变形将进一步增加,且在后期的稳定性具有减弱的趋势,与预测的结果一致。通过研究,验证了组合预测及R/S分析在基坑变形趋势判断中的有效性,这为基坑变形预测及趋势判断提供了一种新的思路。

Effective forecasting model for foundation pit’s deformation trend could guide construction and avoid accidents. In this article, GM (1,1), support vector machine and BP neural network were employed for single forecasting of pit deformation, and combinatorial forecasting models with fixed-weight and non-fixed weight were also established. Furthermore, R/S analysis was carried out to determine the deformation trend and verify the effectiveness of the combinatorial forecasting results. Results suggest that combinatorial forecasting could effectively improve the stability and precision of the prediction results, among which combinatorial BP neural network has the optimal results with the measured values and predicted values in good agreement. Moreover, the deformation of foundation pit will further increase and the stability has trend of weakening, in consistency with forecasting results. The research verified the effectiveness of combinatorial forecasting and R/S analysis in judging the deformation trend of foundation pit, and provided a new idea for the prediction of foundation pit deformation.