A Machine Learning Architecture Replacing Heavy Instrumented Laboratory Tests: In Application to the Pullout Capacity of Geosynthetic Reinforced Soils

A Machine Learning Architecture Replacing Heavy Instrumented Laboratory Tests: In Application to the Pullout Capacity of Geosynthetic Reinforced Soils

For economical and sustainable benefits, conventional retaining walls are being replaced by geosynthetic reinforced soil (GRS). However, for safety and quality assurance purposes, prior tests of pullout capacities of these materials need to be performed. Conventionally, these tests are conducted in...

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Bibliographic Details
Main Authors: Tabish Ali, Waseem Haider, Nazakat Ali, Muhammad Aslam
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Sensors
Subjects:
geosynthetic reinforced soil
ANN
machine learning
pullout capacity
weathered granite soil
Bayesian regularization
Online Access:https://www.mdpi.com/1424-8220/22/22/8699

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