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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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S131915782100330X |
| _version_ | 1811184011523915776 |
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| author | Preeti Monga Manik Sharma Sanjeev Kumar Sharma |
| author_facet | Preeti Monga Manik Sharma Sanjeev Kumar Sharma |
| author_sort | Preeti Monga |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T13:06:09Z |
| format | Article |
| id | doaj.art-7eb39c53c3ac44c49c62fd53edfd66e8 |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-04-11T13:06:09Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-7eb39c53c3ac44c49c62fd53edfd66e82022-12-22T04:22:45ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782022-11-01341096229643A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trendPreeti Monga0Manik Sharma1Sanjeev Kumar Sharma2Corresponding author.; Department of CSA, DAV University, IndiaDepartment of CSA, DAV University, IndiaDepartment of CSA, DAV University, IndiaThis 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.http://www.sciencedirect.com/science/article/pii/S131915782100330XSwarm intelligenceFeature selectionHealthcareMeta-heuristicsResearch trend |
| spellingShingle | Preeti Monga Manik Sharma Sanjeev Kumar Sharma A comprehensive meta-analysis of emerging swarm intelligent computing techniques and their research trend Journal of King Saud University: Computer and Information Sciences Swarm intelligence Feature selection Healthcare Meta-heuristics Research trend |
| title | 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_short | 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 |
| topic | Swarm intelligence Feature selection Healthcare Meta-heuristics Research trend |
| url | http://www.sciencedirect.com/science/article/pii/S131915782100330X |
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