Estimation of load capacity of driven piles by COA–MLP and COA–SVR models: a comparative study-Reference-Cited by-同舟云学术

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Estimation of load capacity of driven piles by COA–MLP and COA–SVR models: a comparative study

Published:2023-07-26 Issue: Volume: Page:
ISSN:2520-8160
Container-title:Multiscale and Multidisciplinary Modeling, Experiments and Design
language:en
Short-container-title:Multiscale and Multidiscip. Model. Exp. and Des.

Author:

Song Yuhua

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Mechanics of Materials,General Materials Science

Link

https://link.springer.com/content/pdf/10.1007/s41939-023-00195-4.pdf

Reference56 articles.

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2. Alkroosh I, Nikraz H (2014) Predicting pile dynamic capacity via application of an evolutionary algorithm. Soils Found 54:233–242

3. Alkroosh IS, Bahadori M, Nikraz H, Bahadori A (2015) Regressive approach for predicting bearing capacity of bored piles from cone penetration test data. J Rock Mech Geotech Eng 7:584–592

4. Alzahrani S, Bilgin Ö (2023) Prediction of pile setup for driven pipe piles in fine-grained soils using gene expression programming. Geotechn Geol Eng 41:3605–3624

5. Ardalan H, Eslami A, Nariman-Zadeh N (2009) Piles shaft capacity from CPT and CPTu data by polynomial neural networks and genetic algorithms. Comput Geotech 36:616–625

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1. Evaluation of driven piles’ load capacity by optimization-based prediction algorithms;International Journal on Interactive Design and Manufacturing (IJIDeM);2024-06-09

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