1) predicting pile figure
桩形预测
2) peredict pile-sinking
沉桩预测
3) stability forecast of anti-slide pile
抗滑桩稳定预测
4) predicting settlement of single pile
单桩沉降预测
1.
Neural networks simplified model of predicting settlement of single pile
单桩沉降预测的神经网络简化模型
5) flatness prediction
板形预测
1.
Finally,an ideal flatness prediction model,based on BP neural network,is established so that the prediction of the flatness parameters in rolling operation can be accomplished.
通过有限元仿真分析,较准确的模拟了带钢轧制过程,获取对轧机板形影响较大的参数值,并将其结果作为训练样本对神经网络进行训练,建立了较为理想的基于神经网络的板形预测模型,实现了轧制过程中的板形参数的预报。
6) 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
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。
参考词条