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1)  prediction of ground deformation
地表变形预测
1.
A study of prediction of ground deformation with small samples in shield construction in soft clays using ENN method;
对上海市某盾构隧道的施工地表变形预测表明该模型可获得较高预测精度。
2)  ground deformation prediction
地面变形预测
3)  deformation prediction
变形预测
1.
Application of cubic exponential smoothing method to city underground deformation prediction;
三次指数平滑法在城市地铁变形预测中的应用
2.
The wavelet neural network based on the Extended Kalman Filter applied to deformation prediction;
基于EKF的小波神经网络在变形预测中的应用
3.
Application of neural network based on the extended Kalman filter to deformation prediction;
基于EKF的神经网络在变形预测中的应用
4)  deformation forecast
变形预测
1.
Subgrade deformation forecast of frozen soil based on phase space reconstruction;
基于相空间重构的冻土路基变形预测
2.
Application of gray model in deformation forecast of foundation pit support;
灰色模型在基坑支护变形预测中的有效应用
3.
Application of dynamic gray model in deformation forecast;
动态灰色模型在变形预测中的应用
5)  deformation forecasting
变形预测
1.
Application of the multi-wavelet nervous network in the deformation forecasting;
多小波神经网络在变形预测中的应用
2.
Research on deformation forecasting of deep foundationpit supporting structure based on neural networks;
基于神经网络的深基坑支护结构变形预测研究
3.
The application of self adaptive GM(1,1) gray model in foundation deformation forecasting;
自适应GM(1,1)灰色模型在基坑变形预测中的应用
6)  displacement prediction
变形预测
1.
Aiming at the importance of deformation control in deep foundation pits,this paper presents the displacement prediction model based on artificial neural network,a case shows that the dynamic and real-time ANN prediction technique can solve the factual problems successfully.
针对深基坑支护结构变形控制的重要性,提出了基于人工神经网络技术的变形预测模型,实例计算说明,动态、实时的神经网络预测方法能够很好地解决工程实际问题。
2.
Considering on the monotonously increasing character of the displacement series in underground engineering, a new integrated intelligent method for displacement prediction is proposed.
针对地下工程变形监测中位移单调增长的特性 ,根据位移分解原理 ,采用灰色系统提取位移序列的趋势 ,用基于免疫进化规划的进化神经网络逼近偏差序列 ,提出了变形预测的集成智能建模方法 ,很好地解决了地下工程变形预测的难题。
补充资料:发育进度预测法(见发生期预测)


发育进度预测法(见发生期预测)


  发育进度预测法见发生期预测。
  
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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