论文部分内容阅读
地铁施工导致的地表沉降问题日益突出,对其进行监测控制也愈发重要。采用时间序列ARMA模型对监测数据进行分析处理,并以过去一段时期的实测沉降值为依据进行沉降预报预测。结果表明当以实时监测数据为依据进行预测时,预测结果与实际情况基本吻合,精度较高;当进行多步预测时,预测结果精度低,误差大。故在工程实际中对地表沉降进行预测时,应当保持监测数据的频率和监测数据的事实有效性。
Subway construction caused by surface subsidence problems have become increasingly prominent, its monitoring and control is also increasingly important. The time series ARMA model was used to analyze and process the monitoring data, and the subsidence forecast was made based on the measured settlement value of the past period. The results show that when the prediction is based on real-time monitoring data, the prediction results are in good agreement with the actual situation and the accuracy is high. When the multi-step prediction is made, the prediction accuracy is low and the error is large. Therefore, when predicting surface subsidence in engineering practice, the frequency of monitoring data and the factual validity of monitoring data should be maintained.