该方法按数学模型对子系统进行结构水平上的分解，运用层次分析法来处理数据获得对子系统的仿真可信性的评估。
This approach analyzes sub-system on the level of construction due to it's digital model , and it gets the system's general credibility with AHP to process data.
采用经验模式分解(EMD)与小波分析相结合的方法探讨结构响应数据信号，进行建筑结构损伤检测诊断。
The use of empirical mode decomposition (EMD) method and wavelet analysis in combination is explored for the detection of changes in the structural response data from structural damage diagnosis.
基于前馈神经网络的权重分析，提出一种基于神经网络的结构优化层次分解方法，较好地解决了这一问题。
Based on weights analysis of feedforward neural networks, a hierarchic decomposition neural networks method for solving this problem is provided.
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