Cargando…

A comprehensive database of Nature-Inspired Algorithms

These data contain a comprehensive collection of all Nature-Inspired Algorithms. This collection is a result of two corresponding surveys, where all Nature-Inspired Algorithms that have been published to-date were gathered and preliminary data acquired. The rapidly increasing number of nature-inspir...

Descripción completa

Detalles Bibliográficos
Autores principales: Tzanetos, Alexandros, Fister, Iztok, Dounias, Georgios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7300069/
https://www.ncbi.nlm.nih.gov/pubmed/32577446
http://dx.doi.org/10.1016/j.dib.2020.105792
_version_ 1783547509170241536
author Tzanetos, Alexandros
Fister, Iztok
Dounias, Georgios
author_facet Tzanetos, Alexandros
Fister, Iztok
Dounias, Georgios
author_sort Tzanetos, Alexandros
collection PubMed
description These data contain a comprehensive collection of all Nature-Inspired Algorithms. This collection is a result of two corresponding surveys, where all Nature-Inspired Algorithms that have been published to-date were gathered and preliminary data acquired. The rapidly increasing number of nature-inspired approaches makes it hard for interested researchers to keep up. Moreover, a proper taxonomy is necessary, based on specific features of the algorithms. Different taxonomies and useful insight into the application areas that the algorithms have coped with is given through these data. This article provides a detailed description of the above mentioned collection.
format Online
Article
Text
id pubmed-7300069
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-73000692020-06-22 A comprehensive database of Nature-Inspired Algorithms Tzanetos, Alexandros Fister, Iztok Dounias, Georgios Data Brief Computer Science These data contain a comprehensive collection of all Nature-Inspired Algorithms. This collection is a result of two corresponding surveys, where all Nature-Inspired Algorithms that have been published to-date were gathered and preliminary data acquired. The rapidly increasing number of nature-inspired approaches makes it hard for interested researchers to keep up. Moreover, a proper taxonomy is necessary, based on specific features of the algorithms. Different taxonomies and useful insight into the application areas that the algorithms have coped with is given through these data. This article provides a detailed description of the above mentioned collection. Elsevier 2020-06-02 /pmc/articles/PMC7300069/ /pubmed/32577446 http://dx.doi.org/10.1016/j.dib.2020.105792 Text en © 2020 The Author(s). Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Tzanetos, Alexandros
Fister, Iztok
Dounias, Georgios
A comprehensive database of Nature-Inspired Algorithms
title A comprehensive database of Nature-Inspired Algorithms
title_full A comprehensive database of Nature-Inspired Algorithms
title_fullStr A comprehensive database of Nature-Inspired Algorithms
title_full_unstemmed A comprehensive database of Nature-Inspired Algorithms
title_short A comprehensive database of Nature-Inspired Algorithms
title_sort comprehensive database of nature-inspired algorithms
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7300069/
https://www.ncbi.nlm.nih.gov/pubmed/32577446
http://dx.doi.org/10.1016/j.dib.2020.105792
work_keys_str_mv AT tzanetosalexandros acomprehensivedatabaseofnatureinspiredalgorithms
AT fisteriztok acomprehensivedatabaseofnatureinspiredalgorithms
AT douniasgeorgios acomprehensivedatabaseofnatureinspiredalgorithms
AT tzanetosalexandros comprehensivedatabaseofnatureinspiredalgorithms
AT fisteriztok comprehensivedatabaseofnatureinspiredalgorithms
AT douniasgeorgios comprehensivedatabaseofnatureinspiredalgorithms