✦ LIBER ✦

A neural network model for liquefaction-induced horizontal ground displacement

✍ Scribed by J. Wang; M.S. Rahman

Publisher: Elsevier Science
Year: 1999
Tongue: English
Weight: 588 KB
Volume: 18
Category: Article
ISSN: 0267-7261
DOI: 10.1016/s0267-7261(99)00027-5

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✦ Synopsis

The horizontal ground displacement generated by seismically induced liquefaction is known to produce significant damage to engineered structures. A backpropagation neural network model is developed to predict the horizontal ground displacements. A large database containing the case histories of lateral spreads observed in eight major earthquakes is used. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the amount of horizontal ground displacement. As more data become available, the model itself can be improved to make more accurate displacement prediction for a wider range of earthquake and site conditions.

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