Data-Driven Modeling of Peak Rotation and Tipping-Over Stability of Rocking Shallow Foundations Using Machine Learning Algorithms

Data-Driven Modeling of Peak Rotation and Tipping-Over Stability of Rocking Shallow Foundations Using Machine Learning Algorithms

The objective of this study is to develop data-driven predictive models for peak rotation and factor of safety for tipping-over failure of rocking shallow foundations during earthquake loading using multiple nonlinear machine learning (ML) algorithms and a supervised learning technique. Centrifuge a...

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Bibliographic Details
Main Author: Sivapalan Gajan
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Geotechnics
Subjects:
rocking foundations
earthquake engineering
soil-structure interaction
tipping-over stability
machine learning
Online Access:https://www.mdpi.com/2673-7094/2/3/38

Internet

https://www.mdpi.com/2673-7094/2/3/38

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