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【目的】基坑变形的监测是保证基坑施工安全的重要保障，为提高监测数据的应用价值及确保基坑的施工安全，以陕西省西安市某330 kV变电站基坑工程为项目依托，基于实际变形监测结果【方法】以均方误差MSE作为遗传算法(GA)的适应度函数，对Prophet模型中的趋势项、周期项和节假日项(偶发事件项)参数进行优化，并重点考虑与基坑变形规律相一致的趋势项参数，构建GA-Prophet基坑变形预测模型，并以MAE、RSS、RMSE和Theil不等系数值为评价指标，验证本模型的可行性及有效性，同时使用该模型对基坑水平及竖向变形进行超前预测，以评价基坑结构的安全状态。【结果】结果表明：GA-Prophet模型预测结果曲线与实测数据曲线较为接近，归功于预测模型中选用了符合实际工程位移变化规律的饱和模型，以JC8测点水平位移预测结果为例，该模型预测结果的MAE、RSS、RMSE、Theil不等系数值分别为0.480、1.310、0.512和0.052,均优于Prophet、LSTM、ARIMA和BP模型的预测结果；并且该模型对基坑变形的超前预测结果显示，各测点水平及竖向变形预测最大值均未超过规范要求的变形报警值，基坑结构处于安全状态。【结论】该模型对于基坑变形预测具有较好的适用性，提高了预测结果的准确性，可用于基坑变形安全预测。
Abstract：[Objective]Monitoring the deformation of foundation pits is crucial to ensuring the safe construction of foundation pits. To enhance the application value of monitoring data and ensure the safety of foundation pit construction, this study relies on a 330kV substation foundation pit project in Xi'an, Shaanxi Province, and is based on actual deformation monitoring result.[Methods]Using the mean square error(MSE) as the fitness function of the genetic algorithm(GA), the trend, seasonality, and holiday(sporadic event) parameters of the Prophet model were optimized, with particular attention to the trend parameters consistent with the deformation pattern of the foundation pit. The GA-Prophet foundation pit deformation prediction model was constructed, and its feasibility and effectiveness were verified using evaluation metrics such as MAE, RSS, RMSE, and Theil Inequality Coefficient values. Additionally, this model was employed for the early prediction of horizontal and vertical deformation of the foundation pit to evaluate the safety status of the foundation pit structure.[Results]The result indicate that the prediction curve of the GA-Prophet model closely aligns with the measured data curve, attributed to the adoption of a saturation model that conforms to the actual engineering displacement change pattern in the prediction model. Taking the horizontal displacement prediction result of the JC8 measurement point as an example, the MAE, RSS, RMSE, and Theil Inequality Coefficient values of the prediction result were 0.480, 1.310, 0.512, and 0.052, respectively, all superior to the prediction result of the Prophet, LSTM, ARIMA, and BP models. Moreover, the early prediction result of foundation pit deformation by this model show that the maximum predicted values of horizontal and vertical deformation at each measurement point did not exceed the deformation alarm values specified by the standards, indicating that the foundation pit structure is in a safe state.[Conclusion]The model demonstrates good applicability for predicting foundation pit deformation and improves the accuracy of the prediction result. It can be used for the safety prediction of foundation pit deformation.
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基本信息:
DOI：10.13928/j.cnki.wrahe.2025.04.009
中图分类号:TU433;TM63
引用信息:
[1]王文强,燕波,齐壮,等.基于GA-Prophet模型的变电站基坑变形安全预测研究与应用[J].水利水电技术(中英文),2025,56(04):107-117.DOI:10.13928/j.cnki.wrahe.2025.04.009.
基金信息:
国家自然科学基金面上项目(42177132); 四川省自然科学基金项目(24NSFSC4618); 陕西省教育厅服务地方专项科研计划项目(21JC009); 渭南市重点研发计划项目(2023ZDYFJH-424)