中文摘要：

The multi-layers feedforward neural network is used for inversion of material constants of flu-id-saturated porous media.The direct analysis of fluid-saturated porous media is carried out with the bound-ary element method.The dynamic displacement responses obtained from direct analysis for prescribed materi-al parameters constitute the sample sets training neural network.By virtue of the effective L-M training algo-rithm and the Tikhunov regularization method as well as the GCV method for an appropriate selection of regu-larization parameter,the inverse mapping from dynamic displacement responses to material constants is per-formed.Numerical examples demonstrate the validity of the neural network method.

英文摘要：

The multi- layers feedforward neural network is used for inversion ofmaterial constants of fluid-saturated porous media. The direct analysis of fluid-saturated porousmedia is carried out with the boundary element method. The dynamic displacement responses obtainedfrom direct analysis for prescribed material parameters constitute the sample sets training neuralnetwork. By virtue of the effective L-M training algorithm and the Tikhonov regularization method aswell as the GCV method for an appropriate selection of regu-larization parameter, the inversemapping from dynamic displacement responses to material constants is performed. Numerical examplesdemonstrate the validity of the neural network method.