Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/61392
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kashani, Ali R | en |
dc.contributor.author | Chiong, Raymond | en |
dc.contributor.author | Mirjalili, Seyedali | en |
dc.contributor.author | Gandomi, Amir H | en |
dc.date.accessioned | 2024-07-10T01:01:06Z | - |
dc.date.available | 2024-07-10T01:01:06Z | - |
dc.date.issued | 2021-05 | - |
dc.identifier.citation | Archives of Computational Methods in Engineering, 28(3), p. 1871-1927 | en |
dc.identifier.issn | 1886-1784 | en |
dc.identifier.issn | 1134-3060 | en |
dc.identifier.uri | https://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.language | en | en |
dc.publisher | Springer Dordrecht | en |
dc.relation.ispartof | Archives of Computational Methods in Engineering | en |
dc.title | Particle Swarm Optimization Variants for Solving Geotechnical Problems: Review and Comparative Analysis | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1007/s11831-020-09442-0 | en |
local.contributor.firstname | Ali R | en |
local.contributor.firstname | Raymond | en |
local.contributor.firstname | Seyedali | en |
local.contributor.firstname | Amir H | en |
local.profile.school | School of Science & Technology | en |
local.profile.email | rchiong@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | The Netherlands | en |
local.format.startpage | 1871 | en |
local.format.endpage | 1927 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 28 | en |
local.identifier.issue | 3 | en |
local.title.subtitle | Review and Comparative Analysis | en |
local.contributor.lastname | Kashani | en |
local.contributor.lastname | Chiong | en |
local.contributor.lastname | Mirjalili | en |
local.contributor.lastname | Gandomi | en |
dc.identifier.staff | une-id:rchiong | en |
local.profile.orcid | 0000-0002-8285-1903 | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/61392 | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Particle Swarm Optimization Variants for Solving Geotechnical Problems | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Kashani, Ali R | en |
local.search.author | Chiong, Raymond | en |
local.search.author | Mirjalili, Seyedali | en |
local.search.author | Gandomi, Amir H | en |
local.uneassociation | No | en |
dc.date.presented | 2021 | - |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.published | 2021 | en |
local.year.presented | 2021 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/5e2351d4-3cac-4441-a7c6-8f7438371dfc | en |
local.subject.for2020 | 4602 Artificial intelligence | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.date.moved | 2024-08-26 | en |
Appears in Collections: | Journal Article School of Science and Technology |
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