Prediction of Internal Stability for Geogrid-Reinforced Segmental Walls

Anuar Kasa; Zamri Chik; Mohd Raihan Taha

doi:10.4028/www.scientific.net/AMR.163-167.1854

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 163-167Prediction of Internal Stability for...

Prediction of Internal Stability for Geogrid-Reinforced Segmental Walls

Abstract:

Prediction of internal stability for segmental retaining walls reinforced with geogrid and backfilled with residual soil was carried out using statistical methods and artificial neural networks (ANN). Prediction was based on data obtained from 234 segmental retaining wall designs using procedures developed by the National Concrete Masonry Association (NCMA). The study showed that prediction made using ANN was generally more accurate to the target compared with statistical methods using mathematical models of linear, pure quadratic, full quadratic and interactions.

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Periodical:

Advanced Materials Research (Volumes 163-167)

Pages:

1854-1857

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.163-167.1854

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Online since:

December 2010

Authors:

Anuar Kasa, Zamri Chik, Mohd Raihan Taha

Keywords:

Artificial Neural Network (ANN), Geogrid, Modular Block, Segmental Retaining Wall, Statistical Method

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References

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