Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61392
Full metadata record
DC FieldValueLanguage
dc.contributor.authorKashani, Ali Ren
dc.contributor.authorChiong, Raymonden
dc.contributor.authorMirjalili, Seyedalien
dc.contributor.authorGandomi, Amir Hen
dc.date.accessioned2024-07-10T01:01:06Z-
dc.date.available2024-07-10T01:01:06Z-
dc.date.issued2021-05-
dc.identifier.citationArchives of Computational Methods in Engineering, 28(3), p. 1871-1927en
dc.identifier.issn1886-1784en
dc.identifier.issn1134-3060en
dc.identifier.urihttps://hdl.handle.net/1959.11/61392-
dc.description.abstract<p>Optimization techniques have drawn much attention for solving geotechnical engineering problems in recent years. Particle swarm optimization (PSO) is one of the most widely used population-based optimizers with a wide range of applications. In this paper, we frst provide a detailed review of applications of PSO on diferent geotechnical problems. Then, we present a comprehensive computational study using several variants of PSO to solve three specifc geotechnical engineering benchmark problems: the retaining wall, shallow footing, and slope stability. Through the computational study, we aim to better understand the algorithm behavior, in particular on how to balance exploratory and exploitative mechanisms in these PSO variants. Experimental results show that, although there is no universal strategy to enhance the performance of PSO for all the problems tackled, accuracies for most of the PSO variants are signifcantly higher compared to the original PSO in a majority of cases.</p>en
dc.languageenen
dc.publisherSpringer Dordrechten
dc.relation.ispartofArchives of Computational Methods in Engineeringen
dc.titleParticle Swarm Optimization Variants for Solving Geotechnical Problems: Review and Comparative Analysisen
dc.typeJournal Articleen
dc.identifier.doi10.1007/s11831-020-09442-0en
local.contributor.firstnameAli Ren
local.contributor.firstnameRaymonden
local.contributor.firstnameSeyedalien
local.contributor.firstnameAmir Hen
local.profile.schoolSchool of Science & Technologyen
local.profile.emailrchiong@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeThe Netherlandsen
local.format.startpage1871en
local.format.endpage1927en
local.peerreviewedYesen
local.identifier.volume28en
local.identifier.issue3en
local.title.subtitleReview and Comparative Analysisen
local.contributor.lastnameKashanien
local.contributor.lastnameChiongen
local.contributor.lastnameMirjalilien
local.contributor.lastnameGandomien
dc.identifier.staffune-id:rchiongen
local.profile.orcid0000-0002-8285-1903en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/61392en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleParticle Swarm Optimization Variants for Solving Geotechnical Problemsen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorKashani, Ali Ren
local.search.authorChiong, Raymonden
local.search.authorMirjalili, Seyedalien
local.search.authorGandomi, Amir Hen
local.uneassociationNoen
dc.date.presented2021-
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2021en
local.year.presented2021en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/5e2351d4-3cac-4441-a7c6-8f7438371dfcen
local.subject.for20204602 Artificial intelligenceen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-08-26en
Appears in Collections:Journal Article
School of Science and Technology
Files in This Item:
1 files
File SizeFormat 
Show simple item record

SCOPUSTM   
Citations

45
checked on Oct 26, 2024

Page view(s)

84
checked on Aug 3, 2024
Google Media

Google ScholarTM

Check

Altmetric


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.