Estimation of ultimate bearing capacity of driven piles in c-φ soil using MLP-GWO and ANFIS-GWO models: a comparative study-Reference-Cited by-同舟云学术

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Estimation of ultimate bearing capacity of driven piles in c-φ soil using MLP-GWO and ANFIS-GWO models: a comparative study

Published:2020-11-19 Issue:5 Volume:25 Page:4103-4119
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Dehghanbanadaki Ali,Khari Mahdy,Amiri Shin To,Armaghani Danial Jahed

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-020-05435-0.pdf

Reference86 articles.

1. Ahmad I, El Naggar MH, Khan AN (2007) Artificial neural network application to estimate kinematic soil pile interaction response parameters. Soil Dyn Earthq Eng 27(9):892–905

2. Akay B, Karaboga D (2011) Wavelet packets optimization using artificial bee colony algorithm. In: 2011 IEEE Congress on evolutionary computation (CEC), IEEE, 89–94

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

4. 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 7(5):584–592

5. Ardakani A, Kordnaeij A (2019) Soil compaction parameters prediction using GMDH-type neural network and genetic algorithm. Eur J Environ Civ En 23(4):449–462

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