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An evolutionary based approach for assessment of earthquake-induced soil liquefaction and lateral displacement

An evolutionary based approach for assessment of earthquake-induced soil liquefaction and lateral displacement

Rezania, Mohammad, Faramarzi, Asaad and Javadi, Akbar A. (2011) An evolutionary based approach for assessment of earthquake-induced soil liquefaction and lateral displacement. Engineering Applications of Artificial Intelligence, 24 (1). pp. 142-153. ISSN 0952-1976 (doi:https://doi.org/10.1016/j.engappai.2010.09.010)

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Abstract

Prediction of liquefaction and the resulting lateral displacement is a complex engineering problem due to heterogeneous nature of soils and participation of a large number of factors involved. In this paper new models are developed, based on evolutionary polynomial regression (EPR), for assessment of liquefaction potential and lateral spreading. The models developed for liquefaction and lateral spreading are compared to those obtained from neural network and linear regression based techniques. It is shown that the developed models are able to learn the complex relationship between either of these problems and their contributing factors in the form of a function with high level of accuracy (mostly in excess of 90%). The results of the EPR model developed for the liquefaction determination are used to find a novel 3-D boundary surface that discriminates between the cases of occurrence and non-occurrence of liquefaction. The developed boundary surface is employed to calculate the factor of safety against liquefaction occurrence.

Item Type: Article
Additional Information: [1] Available online 28 October 2010. [2] Supplementary data associated with this article can be found in the online version at doi:10.1016/j.engappai.2010.09.010.
Uncontrolled Keywords: earthquake, liquefaction, lateral displacement, evolutionary regression
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Pre-2014 Departments: School of Engineering
Related URLs:
Last Modified: 14 Oct 2016 09:23
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/9582

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