Prediction of time-dependent bearing capacity of concrete pile in cohesive soil using optimized relevance vector machine and long short-term memory models

Abstract The present investigation employs relevance vector machine (RVM) and long short-term memory (LSTM) models to predict the time-dependent bearing capacity of concrete piles. Each RVM model (SRVM) is configured by each linear, polynomial, gaussian, sigmoid, laplacian, and exponential kernel fu...

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Bibliographic Details
Main Authors:	Jitendra Khatti, Mohammadreza Khanmohammadi, Yewuhalashet Fissha
Format:	Article
Language:	English
Published:	Nature Portfolio 2024-12-01
Series:	Scientific Reports
Subjects:	Concrete piles Multicollinearity Time-dependent bearing capacity Hybrid relevance vector machine Long short-term memory
Online Access:	https://doi.org/10.1038/s41598-024-83784-8
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Prediction of time-dependent bearing capacity of concrete pile in cohesive soil using optimized relevance vector machine and long short-term memory models

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