Location

St. Louis, Missouri

Session Start Date

4-2-1995

Session End Date

4-7-1995

Abstract

Neural networks have emerged as a powerful computational technique for modeling nonlinear multivariate relationships. The neural network is a product of artificial intelligence research. This paper examines the feasibility of using neural networks for assessing liquefaction potential, from actual field records. The paper starts with a brief overview of the basic architecture and concepts of neural networks. The application of the neural network methodology to evaluate seismic liquefaction potential is then presented.

Department(s)

Civil, Architectural and Environmental Engineering

Appears In

International Conferences on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics

Meeting Name

Third Conference

Publisher

University of Missouri--Rolla

Publication Date

4-2-1995

Document Version

Final Version

Rights

© 1995 University of Missouri--Rolla, All rights reserved.

Document Type

Article - Conference proceedings

File Type

text

Language

English

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Apr 2nd, 12:00 AM Apr 7th, 12:00 AM

Predicting Seismic Liquefaction Using Neural Networks

St. Louis, Missouri

Neural networks have emerged as a powerful computational technique for modeling nonlinear multivariate relationships. The neural network is a product of artificial intelligence research. This paper examines the feasibility of using neural networks for assessing liquefaction potential, from actual field records. The paper starts with a brief overview of the basic architecture and concepts of neural networks. The application of the neural network methodology to evaluate seismic liquefaction potential is then presented.