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- W2385202210 abstract "Based on the analysis of predicting models for the the lateral spread induced by earthquakeliquefaction, the relationships between lateral spread and the measured data of earthquake, topographical and soil factors are discussed. A predicting model of artificial neural networks for lateral spread is presented. The model is capable of reflecting nonlinear relationships between the lateral spread and the influent factors. Results obtained from the model are better consistent with measured data. The correlation factor is above 0.9. The analysis indicates that lateral spread decreases with increasing of distance from freeface, and increases nonlinearly with increasing of thickness of liquefied layer. " @default.
- W2385202210 created "2016-06-24" @default.
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- W2385202210 date "2003-01-01" @default.
- W2385202210 modified "2023-09-25" @default.
- W2385202210 title "A predicting model of artificial neural networks for lateral spread induced by earthquake" @default.
- W2385202210 hasPublicationYear "2003" @default.
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