Location

San Diego, California

Session Start Date

5-24-2010

Session End Date

5-29-2010

Abstract

Though various mechanistic based models are there for prediction of lateral displacement of ground, the statistical/ empirical methods based on the insitu data is most widely used. The artificial neural network method has been extensively used an alternate statistical method in different complex geotechnical engineering problems. Due to inherent difficulty of generalization in artificial neural network method, support vector machine, which is based on statistical learning algorithm is also being used. This paper describes use of extreme learning machine for prediction of large lateral displacement of liquefaction induced ground during an earthquake. Extreme learning machine is an artificial intelligence techniques based on artificial neural network and has been explored here as an alternate statistical method. The results so obtained have been compared with the results obtained using artificial neural network and support vector machine.

Department(s)

Civil, Architectural and Environmental Engineering

Appears In

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

Meeting Name

Fifth Conference

Publisher

Missouri University of Science and Technology

Publication Date

5-24-2010

Document Version

Final Version

Rights

© 2010 Missouri University of Science and Technology, All rights reserved.

Document Type

Article - Conference proceedings

File Type

text

Language

English

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May 24th, 12:00 AM May 29th, 12:00 AM

Prediction of Lateral Displacement of Liquefaction Induced Ground Using Extreme Learning

San Diego, California

Though various mechanistic based models are there for prediction of lateral displacement of ground, the statistical/ empirical methods based on the insitu data is most widely used. The artificial neural network method has been extensively used an alternate statistical method in different complex geotechnical engineering problems. Due to inherent difficulty of generalization in artificial neural network method, support vector machine, which is based on statistical learning algorithm is also being used. This paper describes use of extreme learning machine for prediction of large lateral displacement of liquefaction induced ground during an earthquake. Extreme learning machine is an artificial intelligence techniques based on artificial neural network and has been explored here as an alternate statistical method. The results so obtained have been compared with the results obtained using artificial neural network and support vector machine.