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

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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