关键词: 膨胀土, 胀缩等级, SOM神经网络, 试验验证

Abstract: The existing approaches to identify and classify expansive soil have been evaluated. The indices that can reflect and characterize the swell-shrink mechanism and properties are analyzed. Making use of six indices such as liquid limit, plasticity index, less than two microns glutinous granule percent, CBR, free expansion ratio and CBR expansion ratio, the swelling and shrinking grade model on the theoretic base of SOM neural network model is established through determining the limit value of every, index. And the judgment software is also progrannned. Furtbermore, the judgment model is applied to judge and classify the swelling and shrinking grade of expansive soil samples. The model is tested by other two indices besides the six indices of expansive soil mentioned above, that is, swelling and shrinking performance and strength performance. The classification is proved correct and credible.

Key words: expansive soil , grade of expansion and shrink , SOM neural network , experimental validation ;