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Hybrid artificial electric field employing cuckoo search algorithm with refraction learning for engi...

Hybrid artificial electric field employing cuckoo search algorithm with refraction learning for engi...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6c0047f913e84651a04a85a6fc305d64

Hybrid artificial electric field employing cuckoo search algorithm with refraction learning for engineering optimization problems

About this item

Full title

Hybrid artificial electric field employing cuckoo search algorithm with refraction learning for engineering optimization problems

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2023-03, Vol.13 (1), p.4098-4098, Article 4098

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Due to its low dependency on the control parameters and straightforward operations, the Artificial Electric Field Algorithm (AEFA) has drawn much interest; yet, it still has slow convergence and low solution precision. In this research, a hybrid Artificial Electric Field Employing Cuckoo Search Algorithm with Refraction Learning (AEFA-CSR) is sugge...

Alternative Titles

Full title

Hybrid artificial electric field employing cuckoo search algorithm with refraction learning for engineering optimization problems

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_6c0047f913e84651a04a85a6fc305d64

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6c0047f913e84651a04a85a6fc305d64

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-023-31081-1

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