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Prediction of Internal Stability for Geogrid-Reinforced Segmental Walls
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.
Prediction of Internal Stability for Geogrid-Reinforced Segmental Walls
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.
Prediction of Internal Stability for Geogrid-Reinforced Segmental Walls
Advanced Materials Research ; 163-167 ; 1854-1857
2010-12-06
4 pages
Article (Journal)
Electronic Resource
English
Prediction of Internal Stability for Geogrid-Reinforced Segmental Walls
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