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PREDICTING COLLAPSE POTENTIAL OF SOILS WITH NEURAL NETWORKS.
| 题名： | PREDICTING COLLAPSE POTENTIAL OF SOILS WITH NEURAL NETWORKS. |
| 作者： | Juang-CH; Elton-DJ |
| 关键词： | COLLAPSIBLE-SOILS; PREDICTIONS-; ARTIFICIAL-NEURAL-NETWORKS; INDEX-PROPERTIES; ALGORITHMS- |
| 摘要： | Collapsible soils are known to experience a dramatic decrease in volume upon wetting. This can be very detrimental to structures founded on collapsible soils. Whereas field testing might be the most reliable way to determine collapse potential, the engineer often sees it as the last resort. Neural network models for predicting the collapse potential of soils on the basis of basic index properties are presented. Field data, consisting of index properties and collapse potential, are used to train and test neural networks. Various network architectures and training algorithms are examined and compared. The trained networks are shown to be able to identify the collapsible soils and predict the collapse potential. |
| 总页数： | Transportation Research Record. 1997. (1582) pp22-28 (4 Fig., 3 Tab., 21 Ref.) |
| 报告类型： | 科技报告 |
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