Prediction Of The Settlement Of Highway Soft Soil Foundation By Atificial Neural Network

The distribution of soft soil is very extensive in China , many freeways have to be constructed on the soft foundation due to the restrain of the geographic location. The characteristics of soft soil are: high natural moisture content ratio, high natural void level and high compression ratio. The unfavorable characters of soft soil foundation are: the low carrying capacity, high settlement and long consolidation time. The soft soil consolidation problem of the freeway which construct on the soft soil is a technical tickler. So it is very important to theory and actuality by probing the regularity of soft soil, forecast the final consolidation by the forecast model and methodology from the actual settlement data.From to research the soft soil and soft foundation characteristic the dissertation conclude and sum up the factors which influence the consolidation, introduce some calculate methods by conduct the soft soil deformation and settlement theoretical analysis. The dissertation constructs the forecast foundation settlement BP neural network model by the Harbin freeway soft soil foundation settlement observation data and base the MATLAB artificial neural network(ANN) predicting method. Verify and contrast to the traditional layerwise summation method and the sample training, the advantages of the method are: high degree of accuracy, simple operation, and strong property of general engineering, so it has an width apply prospect.