提出了由两层径基函数(RBF)和两层线性基本函数(LBF)网络组成的串联神经网络模式分类方法。
A cascade neural network composed of double-layer radial basis function (RBF) and linear basis function (LBF) is proposed for pattern classification.
由于准则方程的高次非线性和复杂性，文中利用复合函数求导法则，直接针对基本随机变量求解。
Because of the complexity and high order nonlinear property of the criterion, a derivative method for compound function is used to get reliability.
一次二阶矩方法是结构可靠度分析的基本方法．一次二阶矩方法的计算精度依赖于验算点附近功能函数的非线性程度。
The first-order second-moment method is fundamental in structural reliability analysis, its accuracy depends upon the nonlinear extent of performance functions around checking point.
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