摘要
鉴于使用确定性模型预测隧道涌水量时存在难以准确获取水文地质参数等诸多不便,本文将地下水系统视为"黑箱"模型,通过提取隧道涌水量历史观测数据本身蕴涵的趋势、周期和随机变化规律,建立了隧道涌水的时间序列预测模型。经用于铜锣山隧道实例,反演系列的平均绝对误差为14.67%,预测序列的平均绝对误差为14.34%,表明模型的整体预测精度较高。
Considering inconvenience of obtaining accurate hydrogelogical parameters when using determined model to predict the inflow of tunnel, this paper takes the groundwater system as a ＂black box＂ and establishes a timeseries model to forecast the inflow in tunnel, based on analyzing and extracting the trend component, the periodic component and the stochastic component of the historical observed data. The method is applied to the Tongluoshan tunnel. The Mean Absolute Percent Error （MAPE） of the inversion series is 14.67 %, while the MAPE of the prediction series is 14.34% .The results show that this model has a high prediction accuracy.
出处
《水文地质工程地质》
CAS
CSCD
北大核心
2009年第6期6-9,共4页
Hydrogeology & Engineering Geology
基金
铁道部科技研究开发计划项目(2008G030-B-3)
关键词
隧道涌水
时间序列
随机
反演
预测
inflow in tunnel
time-series
stochastic
inversion
prediction
