The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
A new bio-inspired optimisation algorithm: Bird Swarm Algorithm
Abstract
A new bio-inspired algorithm, namely Bird Swarm Algorithm (BSA), is proposed for solving optimisation applications. BSA is based on the swarm intelligence extracted from the social behaviours and social interactions in bird swarms. Birds mainly have three kinds of behaviours: foraging behaviour, vigilance behaviour and flight behaviour. Birds may forage for food and escape from the predators by the social interactions to obtain a high chance of survival. By modelling these social behaviours, social interactions and the related swarm intelligence, four search strategies associated with five simplified rules are formulated in BSA. Simulations and comparisons based on eighteen benchmark problems demonstrate the effectiveness, superiority and stability of BSA. Some proposals for future research about BSA are also discussed.
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Cites
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Cited by
Rajwar, K., Deep, K., & Das, S. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10470-y · Cited by 687
Feature selection via a novel chaotic crow search algorithm
Sayed, G. I., Hassanien, A. E., & Azar, A. T. (2019) · Neural Computing and Applications · doi:10.1007/s00521-017-2988-6 · Cited by 459
Das, S., & Saha, P. (2021) · Measurement · doi:10.1016/j.measurement.2020.108533 · Cited by 34
Metadata
- Authors
- Meng, X.-B., Gao, X. Z., Lu, L., Liu, Y., & Zhang, H.
- Venue
- Journal of Experimental & Theoretical Artificial Intelligence
- Publisher
- Informa UK Limited
- Published
- 2015-06-17
- Volume
- 28
- Issue
- 4
- Pages
- 673-687
- ISSN
- 0952-813X (ISSN-L)
- 1362-3079
- OpenAlex
- W2237685256
- Cited by
- 469
- References
- 32
- FWCI
- 18.77
- Type
- journal article
- Language
- en
- Open access
- closed
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