The artificial nerve network is used in the deformation forecast of foundation pit in this article, and performs through software MATLAB 7.0 to realize.
将人工神经网络应用于基坑变形预测,并通过软件MATLAB编程加以实现。
参考来源 - 基坑土体参数优化反分析及其变形预测·2,447,543篇论文数据，部分数据来源于NoteExpress
Therefore, the dynamic gray forecast model had higher value than static model in dam deformation forecast.
因此，动态灰色预测模型在大坝变形的预测预报中比静态预测模型具有更高的应用价值。
This article demonstrates that deformation forecast will be performed by a comprehensive method of non linear regression model combined with time series analysis.
本文将讨论综合运用非线性回归模型和时间序列分析的方法进行变形预报。
Off-line forecast shows that fuzzy neural network has high precision in predicting metal plastic deformation resistance.
离线预报表明：模糊神经网络预报金属塑性变形抗力有较高的精度。
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