Mechanical parameters estimation and classification of soils are very important in geologic examination. On the basis of inverse problem theory

a new intelligent method combining RBF neural network and regression analysis is proposed. Then an intellectualized simulation system of soil is established

consisting of two neural networks for mechanical parameter estimation and model recognition. In the system

considering variability of physical parameters is much smaller than mechanical parameters of soils

an artificial neural network model is established to approach the function relationship of the two kinds of parameters. It is effective to reflect mechanical parameters according physical parameters. The mechanical parameters will be input vectors applied to the other network. Then

the new neural network is established; it can offer a good approach to soil classification. This intellectualized simulation system is applied to analyzing geologic examination data in Huangshi; and the results show that the method is simple and effective.