摘要
地下车站施工过程存在严重的安全隐患,为确保施工安全,需要对周围沉降数据进行长期预测,确保未来不会出现较大沉降导致区域塌方。将灰色模型用于沉降预测,使用积分变换替代累加序列进行背景值优化改进,提高背景值的平滑程度,达到提高预测精度的目的。实例验证表明,背景值优化可以在一定程度上提高沉降预测精度,预测残差明显降低。
There are serious potential safety hazards during the construction of the underground station.In order to ensure construction safety,long-term prediction of surrounding subsidence data is required to ensure that there will be no regional collapse caused by large subsidence in the future.The grey model is used for subsidence prediction,and the integral transformation is used to replace the accumulation sequence to optimize and improve the background value,so as to improve the smoothness of the background value and the prediction accuracy.The example shows that the background value optimization can improve the precision of subsidence prediction to a certain extent,and the prediction residual is significantly reduced.
作者
黎湛明
LI Zhanming(Foshan Benchmarking Surveying and Mapping Co.,Ltd.,Foshan 528200,China)
出处
《测绘与空间地理信息》
2022年第12期243-244,249,共3页
Geomatics & Spatial Information Technology
关键词
灰色模型
沉降预测
背景值优化
柯特斯公式
grey model
subsidence prediction
background value optimization
Cotes formula
