Estimating the Pile Settlement Using a Machine Learning Technique Optimized by Henry's Gas Solubility Optimization and Particle Swarm Optimization
Ensuring constructional projects are safe, like stacked structures, requires consideration to immunize structures over the period. Pile settlement (PS) is an important project problem and is receiving a lot of attention to prevent failure before construction starts. Several items for estimating pile...
Saved in:
Main Authors: | Saravana Kumar, Savarimuthu Robinson |
---|---|
Format: | Article |
Language: | English |
Published: |
Bilijipub publisher
2022-12-01
|
Series: | Advances in Engineering and Intelligence Systems |
Subjects: | |
Online Access: | https://aeis.bilijipub.com/article_163964_79fbf8ec9816c1ae968f8abc638e8eb3.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Estimation of the Compressive Strength of Self-Compacting Concrete (SCC) by a Machine Learning Technique Coupling with Novel Optimization Algorithms
by: Ling Chen, et al.
Published: (2023-03-01) -
Appraising the Pile Settlement Rates by Support Vector Regression Optimized Using the Novel Optimization Algorithms
by: Argyros Maris
Published: (2023-06-01) -
Advances in Henry Gas Solubility Optimization: A Physics-Inspired Metaheuristic Algorithm With Its Variants and Applications
by: Mohammed A. El-Shorbagy, et al.
Published: (2024-01-01) -
Coupling Beams’ Shear Capacity Prediction by Hybrid Support Vector Regression and Particle Swarm Optimization
by: Emad A. Abood, et al.
Published: (2025-01-01) -
Investigating the Two Optimization Algorithms (GWO and ACO) Coupling with Radial Basis Neural Network to Estimate the Pile Settlement
by: Ehsanolah Assareh, et al.
Published: (2023-03-01)