A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend
This study presents an extensive analysis of ten emerging swarm intelligence metaheuristic techniques, namely Emperor Penguins Colony (EPC), Harris Hawks Optimizer (HHO), Butterfly Optimization Algorithm (BOA), Spotted Hyena Optimizer (SHO), Crow search algorithm (CSA), Whale optimization algorithm...
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ftdoajarticles:oai:doaj.org/article:7eb39c53c3ac44c49c62fd53edfd66e8 2023-05-15T16:06:00+02:00 A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend Preeti Monga Manik Sharma Sanjeev Kumar Sharma 2022-11-01T00:00:00Z https://doi.org/10.1016/j.jksuci.2021.11.016 https://doaj.org/article/7eb39c53c3ac44c49c62fd53edfd66e8 EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S131915782100330X https://doaj.org/toc/1319-1578 1319-1578 doi:10.1016/j.jksuci.2021.11.016 https://doaj.org/article/7eb39c53c3ac44c49c62fd53edfd66e8 Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 10, Pp 9622-9643 (2022) Swarm intelligence Feature selection Healthcare Meta-heuristics Research trend Electronic computers. Computer science QA75.5-76.95 article 2022 ftdoajarticles https://doi.org/10.1016/j.jksuci.2021.11.016 2022-12-30T20:04:56Z This study presents an extensive analysis of ten emerging swarm intelligence metaheuristic techniques, namely Emperor Penguins Colony (EPC), Harris Hawks Optimizer (HHO), Butterfly Optimization Algorithm (BOA), Spotted Hyena Optimizer (SHO), Crow search algorithm (CSA), Whale optimization algorithm (WOA), Red Deer Algorithm (RDA), Ant Lion Optimizer (ALO), Dragonfly Algorithm (DA) and Grey wolf optimization (GWO). Here, a Quad–fold review strategy comprised of planning, shortlisting, extraction, and execution have been adhered to compile this meta-analysis. The mathematical models and working principles of these techniques have been briefly elucidated. The variants of these meta-heuristic techniques have also been explored and presented. The research trend of these metaheuristic methods has also been highlighted. The findings indicate that these methods are widely used to solve different problems viz: image segmentation, optimal power flow, air pollution forecasting, drug design, wireless sensor networks, disease diagnosis, transport, and routing. Furthermore, in the healthcare sector, the use of SI techniques in selecting optimal features for diagnosis of different diseases like Cancer, Alzheimer's, Kidney disease, Anemia, Viral infection, Skin diseases have also been highlighted. Moreover, it is observed that the education-related optimization problems have been deeply explored by these meta-heuristic techniques whereas, weather forecasting is recognized as the least explored area. The binary, chaotic, and hybrid variants of EPC, HHO, BOA, SHO, CSA, WOA RDA, ALO, DA, and GWO of these metaheuristics techniques need to be deeply explored in healthcare for skin diseases, ophthalmology, viral infection, allergy along with distinct mental disorders. Finally, for better performance, the exploitation and exploration phases of these methods need to be carefully balanced. Article in Journal/Newspaper Emperor penguins Directory of Open Access Journals: DOAJ Articles Boa ENVELOPE(15.532,15.532,66.822,66.822) Journal of King Saud University - Computer and Information Sciences 34 10 9622 9643 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Swarm intelligence Feature selection Healthcare Meta-heuristics Research trend Electronic computers. Computer science QA75.5-76.95 |
spellingShingle |
Swarm intelligence Feature selection Healthcare Meta-heuristics Research trend Electronic computers. Computer science QA75.5-76.95 Preeti Monga Manik Sharma Sanjeev Kumar Sharma A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend |
topic_facet |
Swarm intelligence Feature selection Healthcare Meta-heuristics Research trend Electronic computers. Computer science QA75.5-76.95 |
description |
This study presents an extensive analysis of ten emerging swarm intelligence metaheuristic techniques, namely Emperor Penguins Colony (EPC), Harris Hawks Optimizer (HHO), Butterfly Optimization Algorithm (BOA), Spotted Hyena Optimizer (SHO), Crow search algorithm (CSA), Whale optimization algorithm (WOA), Red Deer Algorithm (RDA), Ant Lion Optimizer (ALO), Dragonfly Algorithm (DA) and Grey wolf optimization (GWO). Here, a Quad–fold review strategy comprised of planning, shortlisting, extraction, and execution have been adhered to compile this meta-analysis. The mathematical models and working principles of these techniques have been briefly elucidated. The variants of these meta-heuristic techniques have also been explored and presented. The research trend of these metaheuristic methods has also been highlighted. The findings indicate that these methods are widely used to solve different problems viz: image segmentation, optimal power flow, air pollution forecasting, drug design, wireless sensor networks, disease diagnosis, transport, and routing. Furthermore, in the healthcare sector, the use of SI techniques in selecting optimal features for diagnosis of different diseases like Cancer, Alzheimer's, Kidney disease, Anemia, Viral infection, Skin diseases have also been highlighted. Moreover, it is observed that the education-related optimization problems have been deeply explored by these meta-heuristic techniques whereas, weather forecasting is recognized as the least explored area. The binary, chaotic, and hybrid variants of EPC, HHO, BOA, SHO, CSA, WOA RDA, ALO, DA, and GWO of these metaheuristics techniques need to be deeply explored in healthcare for skin diseases, ophthalmology, viral infection, allergy along with distinct mental disorders. Finally, for better performance, the exploitation and exploration phases of these methods need to be carefully balanced. |
format |
Article in Journal/Newspaper |
author |
Preeti Monga Manik Sharma Sanjeev Kumar Sharma |
author_facet |
Preeti Monga Manik Sharma Sanjeev Kumar Sharma |
author_sort |
Preeti Monga |
title |
A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend |
title_short |
A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend |
title_full |
A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend |
title_fullStr |
A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend |
title_full_unstemmed |
A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend |
title_sort |
comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend |
publisher |
Elsevier |
publishDate |
2022 |
url |
https://doi.org/10.1016/j.jksuci.2021.11.016 https://doaj.org/article/7eb39c53c3ac44c49c62fd53edfd66e8 |
long_lat |
ENVELOPE(15.532,15.532,66.822,66.822) |
geographic |
Boa |
geographic_facet |
Boa |
genre |
Emperor penguins |
genre_facet |
Emperor penguins |
op_source |
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 10, Pp 9622-9643 (2022) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S131915782100330X https://doaj.org/toc/1319-1578 1319-1578 doi:10.1016/j.jksuci.2021.11.016 https://doaj.org/article/7eb39c53c3ac44c49c62fd53edfd66e8 |
op_doi |
https://doi.org/10.1016/j.jksuci.2021.11.016 |
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Journal of King Saud University - Computer and Information Sciences |
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34 |
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10 |
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9622 |
op_container_end_page |
9643 |
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